{"meta":{"query_hash":"5f94b4c2dd34","filters":{"venue":"Color and Imaging Conference"},"cohort_total":32,"direct_labels_cover":0,"predictions_cover":32,"exported":32,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/5f94b4c2dd34","api":"https://metacan.xera.ac/api/v1/cohort?venue=Color+and+Imaging+Conference"},"results":[{"id":"W111142677","doi":"10.2352/cic.2004.12.1.art00040","title":"Optimal Linear RGB-to-XYZ Mapping for Color Display Calibration","year":2004,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"RGB color model; Color space; Calibration; Artificial intelligence; Computer vision; Color difference; Mathematics; Least-squares function approximation; Computer science; Color management; ICC profile; Graphical display; Liquid-crystal display; Color balance; RGB color space; Color model; Computer graphics (images); Color image; Statistics; Image processing; Image (mathematics)","score_opus":0.01929264285538827,"score_gpt":0.28236736816068564,"score_spread":0.26307472530529735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W111142677","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50468826,0.000007657197,0.49119,0.0025410096,0.00005610489,0.00036521594,0.000036630074,0.000025880754,0.0010892698],"genre_scores_gemma":[0.98579603,0.0000017078412,0.013345081,0.00024827046,0.00012653969,0.00024097147,0.00002738529,0.000006960013,0.00020705225],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993022,0.0000060110415,0.0001370172,0.00026985732,0.00006714721,0.00021776614],"domain_scores_gemma":[0.99959964,0.00004140985,0.000044910117,0.00012381285,0.0000837579,0.00010650081],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008034942,0.00010323217,0.000112520116,0.000043353142,0.00028518392,0.00014261261,0.00013658045,0.000014309776,0.00003909935],"category_scores_gemma":[0.000010052829,0.00009764058,0.000034994904,0.00014984942,0.000071169474,0.00022102309,0.000058978916,0.000058929,0.00001713527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009545245,0.00037676925,0.035846792,0.000058212347,0.00005251327,0.0000022508318,0.0056796833,0.011240962,0.12806848,0.71815985,0.0015855875,0.098833434],"study_design_scores_gemma":[0.0030687463,0.0003451254,0.025892522,0.0001772292,0.00008107206,0.000006126242,0.004448838,0.8344828,0.027914181,0.022973262,0.07945281,0.00115728],"about_ca_topic_score_codex":0.00007196708,"about_ca_topic_score_gemma":0.0000053270014,"teacher_disagreement_score":0.82324183,"about_ca_system_score_codex":0.000016143731,"about_ca_system_score_gemma":0.0001184126,"threshold_uncertainty_score":0.39816672},"labels":[],"label_agreement":null},{"id":"W1530411632","doi":"10.2352/cic.2003.11.1.art00028","title":"A Large Image Database for Color Constancy Research","year":2003,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":216,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Standard illuminant; Color constancy; Artificial intelligence; RGB color model; Color balance; Computer vision; Chromaticity; Computer science; ICC profile; Color space; Color histogram; Color image; Computer graphics (images); Gray (unit); Digital camera; Color model; Image processing; Image (mathematics)","score_opus":0.05597834306926116,"score_gpt":0.38357488974080955,"score_spread":0.3275965466715484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1530411632","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5696913,0.0002459436,0.2938455,0.0027532864,0.00019568185,0.0017824468,0.0007687536,0.00007436882,0.13064271],"genre_scores_gemma":[0.99553823,0.000006631681,0.0031450666,0.000087490735,0.000040705043,0.00033154397,0.000028667677,0.0000071474983,0.0008145085],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989608,0.0000471799,0.0001316,0.00033125997,0.000118261094,0.00041087953],"domain_scores_gemma":[0.9990935,0.00022235519,0.000036507055,0.00023563189,0.00029818082,0.000113837305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005824199,0.000095745054,0.00011944783,0.000059147467,0.00053786155,0.0001976755,0.0001692863,0.000012514556,0.00037440867],"category_scores_gemma":[0.00006375824,0.000090128386,0.00003130385,0.00021843759,0.00027142605,0.00024387811,0.00007131324,0.0001314086,0.000037185102],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000009762159,0.000107224085,0.009374663,0.000012452981,0.000006338414,8.5946317e-7,0.00030717213,1.8157546e-7,0.023639146,0.9572548,0.006388631,0.0028987573],"study_design_scores_gemma":[0.0036081346,0.00018284051,0.0039170426,0.00011495886,0.000060076498,0.000008431564,0.014664394,0.03264959,0.03142769,0.14390527,0.7686164,0.0008451995],"about_ca_topic_score_codex":0.000027943755,"about_ca_topic_score_gemma":0.0000087708695,"teacher_disagreement_score":0.81334955,"about_ca_system_score_codex":0.000011879214,"about_ca_system_score_gemma":0.00022862917,"threshold_uncertainty_score":0.41368505},"labels":[],"label_agreement":null},{"id":"W1764799692","doi":"10.2352/cic.2002.10.1.art00060","title":"Sensor Transforms for Invariant Image Enhancement","year":2002,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer vision; Invariant (physics); Artificial intelligence; Pixel; RGB color model; Mathematics; Computer science","score_opus":0.02243019703477651,"score_gpt":0.2596833120564243,"score_spread":0.2372531150216478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1764799692","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29630286,0.000075964344,0.63949627,0.007051149,0.00010843816,0.00090213853,0.000073738556,0.000047741847,0.05594171],"genre_scores_gemma":[0.9953305,0.00001031047,0.0031066458,0.0001402348,0.000053577038,0.00018566738,0.0000074710038,0.000004397877,0.0011611534],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944407,0.000004838567,0.00010908636,0.00020013326,0.000053610205,0.00018823556],"domain_scores_gemma":[0.9997061,0.000034006778,0.000030159945,0.00010858159,0.0000593529,0.00006182108],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000060629784,0.000082683844,0.00009057954,0.00002195026,0.00018922056,0.000114213144,0.00009846527,0.000007770493,0.0007330018],"category_scores_gemma":[0.0000029567136,0.000070713344,0.000032945718,0.00006615237,0.00008799463,0.00016897892,0.000018365106,0.00004400917,0.000035692883],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001957624,0.0003511924,0.0071743415,0.00004071164,0.000036199923,0.0000013409086,0.0029736203,0.0000031690531,0.25710398,0.24608165,0.007100115,0.4791141],"study_design_scores_gemma":[0.0035804403,0.0003155583,0.0059728613,0.000098990604,0.00014106842,0.000007906525,0.004332777,0.5079673,0.13000292,0.04893827,0.29731336,0.0013285218],"about_ca_topic_score_codex":0.000025347672,"about_ca_topic_score_gemma":0.0000017168003,"teacher_disagreement_score":0.69902766,"about_ca_system_score_codex":0.0000060754824,"about_ca_system_score_gemma":0.0000165037,"threshold_uncertainty_score":0.80258554},"labels":[],"label_agreement":null},{"id":"W2395214674","doi":"10.2352/cic.2013.21.1.art00013","title":"A Robust Hue Descriptor","year":2013,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Categorization, perception, and language","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Hue; Artificial intelligence; Computer science; Computer vision; Pattern recognition (psychology)","score_opus":0.036623484073361155,"score_gpt":0.2646516954574537,"score_spread":0.22802821138409254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2395214674","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.91764253,0.0003619523,0.014939077,0.00085154444,0.00064095913,0.000270388,0.000006287555,0.00013043494,0.065156825],"genre_scores_gemma":[0.9898805,0.000023243198,0.00027968152,0.0006347508,0.00011676942,0.000058040143,0.000017094168,0.0000109087405,0.0089789955],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99935204,0.000037921414,0.00012063092,0.00023358128,0.000057385234,0.00019845288],"domain_scores_gemma":[0.9995727,0.000024394873,0.00003361694,0.00017161983,0.0001163946,0.00008127333],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006188962,0.00009893436,0.00010395022,0.00005334591,0.00010793347,0.00013744365,0.000095903575,0.000036516336,0.013752334],"category_scores_gemma":[0.000021362897,0.000090300084,0.000020277146,0.000076217984,0.00011187535,0.00018754804,0.000025619172,0.00007788665,0.00063358375],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000625738,0.00032431065,0.4387949,0.00007904598,0.00008166747,0.00003290228,0.054893557,0.0000051385136,0.044609956,0.09811665,0.22461574,0.13838354],"study_design_scores_gemma":[0.0007479837,0.000054392818,0.96588314,0.000020397003,0.000027262698,0.0000610012,0.0069250073,0.0031527688,0.00008492737,0.0013936652,0.021328695,0.00032079325],"about_ca_topic_score_codex":0.001053551,"about_ca_topic_score_gemma":0.00007390608,"teacher_disagreement_score":0.5270882,"about_ca_system_score_codex":0.00001307289,"about_ca_system_score_gemma":0.00002607657,"threshold_uncertainty_score":0.98714924},"labels":[],"label_agreement":null},{"id":"W2397853253","doi":"10.2352/cic.2009.17.1.art00049","title":"Sharpening from Shadows: Sensor Transforms for Removing Shadows using a Single Image","year":2009,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer vision; Artificial intelligence; Sharpening; Computer science; Grayscale; Pixel; Entropy (arrow of time)","score_opus":0.03505279020078595,"score_gpt":0.29246101122930296,"score_spread":0.257408221028517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2397853253","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.036204398,0.0003846588,0.95893294,0.0019041885,0.00021176276,0.00036617002,0.000017737571,0.00026729592,0.0017108225],"genre_scores_gemma":[0.5909523,0.00001725263,0.4076609,0.0012107171,0.00007764004,0.0000063535304,0.0000062810195,0.000013073965,0.000055505338],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980805,0.000034075183,0.00036355873,0.00076243177,0.00020194778,0.000557503],"domain_scores_gemma":[0.9989092,0.00016453124,0.00013349272,0.00039758935,0.00020744471,0.00018773835],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00020967251,0.00028857074,0.00034022084,0.00014043978,0.0004149652,0.0008531594,0.0005700209,0.000045794422,0.00002497517],"category_scores_gemma":[0.0001382788,0.00027211313,0.000095212556,0.00022634023,0.000101292564,0.0020591486,0.00012426265,0.0001910848,0.0000063883535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032555967,0.00005010778,0.00023954884,0.000018036175,0.00000800969,0.000023703222,0.0017534501,0.000020048794,0.5009067,0.002650995,0.00008716282,0.4942097],"study_design_scores_gemma":[0.00095771,0.00010021286,0.0010106169,0.00024550676,0.000019680941,0.000049856706,0.00039488342,0.9669572,0.014937483,0.012203047,0.0026547618,0.00046903075],"about_ca_topic_score_codex":0.000042733445,"about_ca_topic_score_gemma":0.0000034205077,"teacher_disagreement_score":0.9669372,"about_ca_system_score_codex":0.00006298308,"about_ca_system_score_gemma":0.00008754914,"threshold_uncertainty_score":0.9999731},"labels":[],"label_agreement":null},{"id":"W2397884703","doi":"10.2352/cic.2006.14.1.art00016","title":"Practical Scene Illuminant Estimation via Flash/No-Flash Pairs","year":2006,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Standard illuminant; Flash (photography); Computer vision; Chromaticity; Artificial intelligence; Computer science; Computer graphics (images); Optics; Physics","score_opus":0.011862109726288834,"score_gpt":0.2774409565456031,"score_spread":0.26557884681931426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2397884703","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4767086,0.00003262756,0.44732496,0.005136225,0.00020773338,0.0004375643,0.00002106485,0.00010672349,0.0700245],"genre_scores_gemma":[0.98944885,0.000001881429,0.009248613,0.00006027637,0.00010954872,0.000052185325,0.000025189784,0.0000058121527,0.001047631],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924153,0.000017497252,0.00015623926,0.00025867982,0.00010856063,0.00021751136],"domain_scores_gemma":[0.9995181,0.00006359973,0.000071444694,0.00015489831,0.00012509667,0.00006684153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001070496,0.000109175606,0.00011105946,0.000033366792,0.00022696599,0.0001569518,0.00009484147,0.000015719072,0.00022459899],"category_scores_gemma":[0.0000126625055,0.00009978771,0.000029749552,0.00012455661,0.00017993638,0.00030287475,0.000057052504,0.00009538162,0.00027645705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032867007,0.0005751183,0.12853558,0.000035600224,0.000023381379,0.000008666462,0.00034890135,0.00012930649,0.0480121,0.31283033,0.037308946,0.4721592],"study_design_scores_gemma":[0.00053703133,0.000060723287,0.059516426,0.000043274442,0.00004952931,0.000011297863,0.0002282073,0.8489352,0.0063114525,0.024855278,0.059013247,0.00043836667],"about_ca_topic_score_codex":0.00018122882,"about_ca_topic_score_gemma":0.000009581173,"teacher_disagreement_score":0.84880584,"about_ca_system_score_codex":0.000012999846,"about_ca_system_score_gemma":0.000092239825,"threshold_uncertainty_score":0.40692246},"labels":[],"label_agreement":null},{"id":"W2398001269","doi":"10.2352/cic.2011.19.1.art00030","title":"Fast Colour Vesselness","year":2011,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Retinal Imaging and Analysis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Artificial intelligence; Computer vision; Grayscale; Computer science; Image (mathematics); Pixel; Hessian matrix; Pattern recognition (psychology); Mathematics","score_opus":0.03855580938296822,"score_gpt":0.2652537808638498,"score_spread":0.2266979714808816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2398001269","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.92618036,0.0003374505,0.0035928746,0.0013315036,0.000091586255,0.000102446436,0.000002527645,0.00009648639,0.06826475],"genre_scores_gemma":[0.9964573,0.00006155931,0.00096306123,0.00048742676,0.000034704713,0.000008293027,0.000004132293,0.000008945436,0.0019745706],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993684,0.000019459078,0.00012415732,0.00021553932,0.000092807226,0.00017960332],"domain_scores_gemma":[0.9995118,0.000018102655,0.000040562638,0.0001555176,0.00014675438,0.00012727438],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009847249,0.00010441848,0.0002054002,0.000071853276,0.00008247438,0.000041384184,0.000066284774,0.000020344862,0.00024909715],"category_scores_gemma":[0.0000509656,0.00008576392,0.000041654817,0.00011541178,0.00017126015,0.0000907648,0.00003964477,0.00011540275,0.000032252396],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026356903,0.00026680643,0.8331281,0.00020643906,0.00012923908,0.000358394,0.0038943233,2.8771862e-7,0.030129211,0.0056594657,0.0028384659,0.123125695],"study_design_scores_gemma":[0.0023023533,0.0003501552,0.92677605,0.00051157025,0.0007504469,0.00071209355,0.004099544,0.027056124,0.021956991,0.0020062006,0.012807439,0.00067103177],"about_ca_topic_score_codex":0.00010454494,"about_ca_topic_score_gemma":0.0000022694462,"teacher_disagreement_score":0.12245466,"about_ca_system_score_codex":0.000010162267,"about_ca_system_score_gemma":0.00006094638,"threshold_uncertainty_score":0.3497351},"labels":[],"label_agreement":null},{"id":"W2398015170","doi":"10.2352/cic.2013.21.1.art00027","title":"Maximum Entropy Spectral Modeling Approach to Mesopic Tone Mapping","year":2013,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Mesopic vision; Color rendering index; Tone mapping; Scotopic vision; Computer science; Artificial intelligence; Photopic vision; Smoothing; Computer vision; Mathematics; Optics; Physics; High dynamic range; Dynamic range","score_opus":0.02270678378251497,"score_gpt":0.24959648449722255,"score_spread":0.22688970071470757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2398015170","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05424945,0.0001071134,0.93230546,0.001634478,0.00011460559,0.00042646326,4.7714553e-7,0.00036305698,0.010798906],"genre_scores_gemma":[0.7327981,0.000014691498,0.26626015,0.00061066594,0.00003505658,0.00008631944,0.0000012369295,0.00000708201,0.00018668223],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99864584,0.00003331906,0.00020726075,0.00050354115,0.00018511909,0.00042491234],"domain_scores_gemma":[0.99926555,0.000017834876,0.000042408417,0.000392755,0.0001454823,0.000135974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001536428,0.00017617423,0.00018427422,0.00013856763,0.00013493901,0.0006301264,0.0006540348,0.000026196627,0.00002960891],"category_scores_gemma":[0.000027437556,0.00016863945,0.000028962879,0.00021419945,0.000048095786,0.0009052638,0.00041573186,0.00013984695,0.00006182625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012958794,0.00031369342,0.0038377838,0.00017795748,0.00005435455,0.000026223837,0.008760843,0.00033388037,0.37799123,0.28128695,0.008104488,0.31909963],"study_design_scores_gemma":[0.00016130872,0.000033203552,0.0010228351,0.00003850251,0.0000032118623,0.000015298996,0.000119016644,0.9769558,0.0076177535,0.013332766,0.00044058025,0.0002597429],"about_ca_topic_score_codex":0.00010341186,"about_ca_topic_score_gemma":6.4637163e-7,"teacher_disagreement_score":0.9766219,"about_ca_system_score_codex":0.000044216144,"about_ca_system_score_gemma":0.000047533453,"threshold_uncertainty_score":0.68769175},"labels":[],"label_agreement":null},{"id":"W2399177186","doi":"10.2352/cic.2011.19.1.art00034","title":"Intersecting Color Manifolds","year":2011,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Burnaby Hospital","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Standard illuminant; RGB color model; Artificial intelligence; Computer vision; Computer science; Color space; RGB color space; Intersection (aeronautics); Manifold (fluid mechanics); Chromaticity; Mathematics; Color image; Image (mathematics); Image processing; Geography","score_opus":0.03154015899057156,"score_gpt":0.2492973886235858,"score_spread":0.21775722963301425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2399177186","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8421062,0.000015861642,0.012851201,0.00020917843,0.00009497324,0.00012660904,0.000005497305,0.000041247513,0.14454922],"genre_scores_gemma":[0.9986657,0.0000013666693,0.00077613775,0.00009310012,0.00004486567,0.00003875366,0.0000028681213,0.000004381759,0.00037284213],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9994738,0.000009348991,0.00010025018,0.00019949586,0.000046805348,0.00017030338],"domain_scores_gemma":[0.9996941,0.00002209927,0.000043739983,0.00012154727,0.00005389746,0.00006460859],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000743832,0.00008025383,0.00008170302,0.00003064418,0.00016838878,0.00007219541,0.00014576837,0.000009080236,0.00062874594],"category_scores_gemma":[0.000003675682,0.000074058575,0.000024436082,0.00009094187,0.0001016614,0.00017193785,0.000084637264,0.00007170483,0.000048728725],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001650453,0.00012728052,0.3937214,0.000008052176,0.000022060598,0.00000327043,0.0056506204,7.5574224e-7,0.017727971,0.4607629,0.000850474,0.12110874],"study_design_scores_gemma":[0.0026111386,0.00044425548,0.5779266,0.00024131566,0.00021829107,0.00004369839,0.05014705,0.10814853,0.05224045,0.14159769,0.06403244,0.0023485725],"about_ca_topic_score_codex":0.00025230952,"about_ca_topic_score_gemma":0.000011778301,"teacher_disagreement_score":0.3191652,"about_ca_system_score_codex":0.00000599437,"about_ca_system_score_gemma":0.000038587375,"threshold_uncertainty_score":0.6884327},"labels":[],"label_agreement":null},{"id":"W2400213164","doi":"10.2352/cic.2007.15.1.art00008","title":"A Standardized Workflow for Illumination-Invariant Image Extraction","year":2007,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Artificial intelligence; Computer vision; Chromaticity; Sharpening; Computer science; Standard illuminant; Invariant (physics); Mathematics","score_opus":0.013490440716148577,"score_gpt":0.306589244271046,"score_spread":0.2930988035548974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2400213164","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1202729,0.000019951114,0.8663197,0.0008766685,0.000087847184,0.00032106153,0.000027435322,0.000029635516,0.012044794],"genre_scores_gemma":[0.98725545,0.0000023397731,0.012113883,0.00005698429,0.000103271195,0.00007316735,0.000016261054,0.000005052633,0.00037360168],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993848,0.0000065961503,0.00013331782,0.00020253268,0.00007724765,0.0001954882],"domain_scores_gemma":[0.99947214,0.00012296173,0.000060383227,0.00010616175,0.00017086558,0.000067512796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031291778,0.00007919568,0.0000906584,0.000044460194,0.00025531728,0.000141234,0.00008295037,0.000012034723,0.0001381252],"category_scores_gemma":[0.000016727543,0.00007531357,0.0000349325,0.000116308714,0.00010421051,0.00025058255,0.000022600165,0.00005681782,0.00000796885],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007725209,0.00011256714,0.010046136,0.000013619117,0.000018188011,0.0000014838373,0.0007770993,0.000003200542,0.11033093,0.2822773,0.0015943097,0.5947479],"study_design_scores_gemma":[0.006532833,0.00026463022,0.14852864,0.00018235046,0.00024041884,0.000017354441,0.010583534,0.15311201,0.12168052,0.26530454,0.29176918,0.0017839968],"about_ca_topic_score_codex":0.000032815235,"about_ca_topic_score_gemma":0.000008005875,"teacher_disagreement_score":0.8669825,"about_ca_system_score_codex":0.000015243647,"about_ca_system_score_gemma":0.00006827299,"threshold_uncertainty_score":0.30711982},"labels":[],"label_agreement":null},{"id":"W2402132597","doi":"10.2352/cic.2012.20.1.art00019","title":"Removing Outliers in Illumination Estimation","year":2012,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"RANSAC; Outlier; Artificial intelligence; Computer science; Image (mathematics); Set (abstract data type); Computer vision; Basis (linear algebra); Sample (material); Pattern recognition (psychology); Base (topology); Standard illuminant; Mathematics","score_opus":0.011883108290174641,"score_gpt":0.27128120757440694,"score_spread":0.2593980992842323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2402132597","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94338775,0.000029079802,0.041082527,0.00055715395,0.00005965861,0.000105379375,0.0000019458726,0.000015352289,0.014761164],"genre_scores_gemma":[0.99866515,9.967513e-7,0.0011227091,0.000038781818,0.000033702676,0.00002491233,0.000006213817,0.000002313907,0.000105202555],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996217,0.000009925881,0.00008038734,0.000095886666,0.000047591082,0.00014450071],"domain_scores_gemma":[0.9998083,0.000025490126,0.000031364605,0.0000662573,0.000024878158,0.000043717024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012909966,0.00004824051,0.00005159115,0.000044397526,0.00008086268,0.00004931353,0.00005284497,0.0000070314914,0.00006258462],"category_scores_gemma":[0.000009176016,0.000047923237,0.000009415255,0.000112449285,0.000051861356,0.0003834253,0.000025722788,0.00004832756,0.000015663258],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000017042953,0.00004639943,0.6140379,0.000003912025,0.000001484983,9.865595e-8,0.0017978572,0.000027219969,0.0034732483,0.08656688,0.00009585557,0.29394746],"study_design_scores_gemma":[0.00031690602,0.0000096198855,0.6957949,0.000033707543,0.000010820947,0.000001518107,0.0029155542,0.28739312,0.0017375343,0.008720769,0.002843591,0.00022198974],"about_ca_topic_score_codex":0.0000784535,"about_ca_topic_score_gemma":0.0000032782516,"teacher_disagreement_score":0.29372546,"about_ca_system_score_codex":0.000012620737,"about_ca_system_score_gemma":0.00002176329,"threshold_uncertainty_score":0.19542529},"labels":[],"label_agreement":null},{"id":"W2403186868","doi":"10.2352/cic.2006.14.1.art00057","title":"Multispectral Colour Constancy","year":2006,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Burnaby Hospital","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multispectral image; RGB color model; Computer science; Artificial intelligence; Computer vision; Color constancy; Image (mathematics)","score_opus":0.004748952167981505,"score_gpt":0.22576973757589555,"score_spread":0.22102078540791403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2403186868","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87521726,0.000065652835,0.018132394,0.0012010224,0.00006872065,0.00017109068,0.000022996479,0.000048316837,0.10507253],"genre_scores_gemma":[0.9983195,0.0000014664299,0.00065501843,0.000056881643,0.000074043484,0.000032391978,0.000008291292,0.000003407052,0.0008489648],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.9994758,0.000007808786,0.00009846115,0.00018408793,0.000055570097,0.00017831275],"domain_scores_gemma":[0.9997415,0.000029107397,0.000035273195,0.000099419034,0.000050235903,0.00004448546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000042158546,0.00007653552,0.00008204439,0.000023340403,0.00017440974,0.000109799585,0.00009476501,0.000008068755,0.0002756285],"category_scores_gemma":[0.0000016745837,0.00007221585,0.000022192566,0.000090875066,0.00015224743,0.00011957852,0.000032922915,0.000060911763,0.00003164115],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000033822664,0.00006569105,0.2828206,0.0000024969395,0.000003841108,0.0000013965066,0.00009194477,0.000005647295,0.01650015,0.6759969,0.0024871444,0.02202081],"study_design_scores_gemma":[0.0018480115,0.00006721548,0.6641807,0.000052183965,0.000057729896,0.000012943788,0.0017842853,0.06368914,0.013916669,0.17226322,0.08121715,0.0009107255],"about_ca_topic_score_codex":0.00035025153,"about_ca_topic_score_gemma":0.000022353308,"teacher_disagreement_score":0.50373363,"about_ca_system_score_codex":0.000006601366,"about_ca_system_score_gemma":0.00005492007,"threshold_uncertainty_score":0.30179387},"labels":[],"label_agreement":null},{"id":"W2405544836","doi":"10.2352/cic.2006.14.1.art00056","title":"Color Constancy for Multiple-Illuminant Scenes using Retinex and SVR","year":2006,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Standard illuminant; Color constancy; Color balance; Artificial intelligence; Computer vision; Computer science; Pixel; Mathematics; Pattern recognition (psychology); Color image; Image (mathematics); Image processing","score_opus":0.015137211531114492,"score_gpt":0.2646034975890739,"score_spread":0.24946628605795942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2405544836","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.95916486,0.00013774025,0.037514634,0.00051932916,0.000056813227,0.0003739479,0.000047203303,0.000022986305,0.0021625145],"genre_scores_gemma":[0.99640816,0.0000046293676,0.0031824464,0.000044415927,0.00008765857,0.00006893805,0.000013110027,0.0000065501927,0.00018408957],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992927,0.000009364271,0.0001490079,0.00027264314,0.00005413086,0.00022216252],"domain_scores_gemma":[0.99954313,0.00011238444,0.000069672016,0.00010749323,0.0001111322,0.00005621309],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000087918954,0.00011234576,0.00013977238,0.00003356085,0.00033974912,0.0001409438,0.00008214313,0.000014832629,0.000024619398],"category_scores_gemma":[0.00001037107,0.0001030292,0.000026841006,0.0000854223,0.00027989803,0.00014396045,0.000052383624,0.000045902005,0.0000016322027],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003532017,0.00011049602,0.6464318,0.000033358883,0.000012280366,0.0000012765839,0.00028182854,0.00002303613,0.13079639,0.18426107,0.0007279527,0.037285205],"study_design_scores_gemma":[0.0029067446,0.00011764831,0.1310591,0.00018074628,0.00013418398,0.000016803704,0.0028499344,0.76426303,0.021316323,0.030403474,0.045788955,0.0009630366],"about_ca_topic_score_codex":0.0003328862,"about_ca_topic_score_gemma":0.00003086311,"teacher_disagreement_score":0.76424,"about_ca_system_score_codex":0.000008467283,"about_ca_system_score_gemma":0.000075319054,"threshold_uncertainty_score":0.42014086},"labels":[],"label_agreement":null},{"id":"W2405792173","doi":"10.2352/cic.2005.13.1.art00024","title":"Shadow Segmentation and Shadow-Free Chromaticity via Markov Random Fields","year":2005,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Standard illuminant; Artificial intelligence; Chromaticity; Pixel; Computer vision; Markov random field; Shadow (psychology); Color constancy; Computer science; Segmentation; Image segmentation; Mathematics; Pattern recognition (psychology); Image (mathematics)","score_opus":0.007667932454304642,"score_gpt":0.24599922869875626,"score_spread":0.23833129624445162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2405792173","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8542244,0.00009369909,0.12631904,0.005782168,0.000048947255,0.00033059026,0.000019406232,0.000038346607,0.013143413],"genre_scores_gemma":[0.9969813,0.000008963288,0.0023838044,0.00025007647,0.00008262287,0.00005581287,0.000009586506,0.0000036299182,0.0002241914],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994224,0.000015557913,0.00012911973,0.00020724979,0.00007578533,0.00014991061],"domain_scores_gemma":[0.9996222,0.00005915845,0.000050260376,0.00015435574,0.000042759155,0.00007123996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000098457946,0.000093864895,0.000112367146,0.000028255967,0.00019942275,0.0001429371,0.0001300188,0.000014304774,0.00028232977],"category_scores_gemma":[0.000006915655,0.000086007116,0.000021069505,0.00007326659,0.00010903274,0.0002711213,0.000090729554,0.0000732733,0.000011485569],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000034143563,0.000119974655,0.07492743,0.000024516201,0.000024267107,7.1004047e-7,0.0014585677,0.000018756804,0.019104443,0.02057397,0.002984909,0.8807283],"study_design_scores_gemma":[0.007446786,0.00014916644,0.19077379,0.00012219182,0.00016529707,0.000017644837,0.002011583,0.67637855,0.023303408,0.0906722,0.007856433,0.0011029283],"about_ca_topic_score_codex":0.00017711219,"about_ca_topic_score_gemma":0.000042478485,"teacher_disagreement_score":0.8796254,"about_ca_system_score_codex":0.000008130211,"about_ca_system_score_gemma":0.000029289604,"threshold_uncertainty_score":0.35072684},"labels":[],"label_agreement":null},{"id":"W2406843677","doi":"10.2352/cic.2005.13.1.art00037","title":"Nonlinear RGB-to-XYZ Mapping for Device Calibration","year":2005,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Optical measurement and interference techniques","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Calibration; RGB color model; Computer vision; Artificial intelligence; Thin plate spline; Computer science; Spline (mechanical); Camera resectioning; Mathematics; Spline interpolation; Physics","score_opus":0.05548126962939465,"score_gpt":0.29623379129624966,"score_spread":0.240752521666855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2406843677","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017002556,0.00006155778,0.9666994,0.00930795,0.000107369364,0.0003433133,0.0000026861835,0.00024258645,0.0062325373],"genre_scores_gemma":[0.77578527,0.000013191849,0.22238484,0.001569213,0.000081139064,0.000050092047,0.0000019798663,0.000004902331,0.00010935877],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991402,0.00001844987,0.00017945032,0.00031210642,0.00011614722,0.00023361767],"domain_scores_gemma":[0.99940306,0.000058794038,0.00003892507,0.00019598751,0.00019634656,0.00010688183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021139147,0.000115680814,0.0001265302,0.00008476158,0.000115725445,0.00035558463,0.00037123862,0.000027519975,0.000013770105],"category_scores_gemma":[0.0001000851,0.00010624336,0.000026497046,0.00013278241,0.00003624332,0.0007162268,0.00013294957,0.00007252964,0.000014542289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000030090256,0.00011814733,0.0029214008,0.00007492528,0.000015914773,0.0000019093052,0.0017710745,0.000007376433,0.1300891,0.13661444,0.0037043516,0.7246513],"study_design_scores_gemma":[0.00029419793,0.00019471362,0.0011543469,0.00012191801,0.000007205265,0.0000052546534,0.00006855391,0.8845675,0.050637953,0.0025860209,0.060039792,0.00032255353],"about_ca_topic_score_codex":0.000007550647,"about_ca_topic_score_gemma":0.00000957338,"teacher_disagreement_score":0.8845601,"about_ca_system_score_codex":0.000026016418,"about_ca_system_score_gemma":0.00005467462,"threshold_uncertainty_score":0.43324783},"labels":[],"label_agreement":null},{"id":"W2895228715","doi":"10.2352/cic.2015.23.1.art00014","title":"Robust Chroma and Lightness Descriptors","year":2015,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Categorization, perception, and language","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Studies; University of British Columbia","funders":"","keywords":"Standard illuminant; Lightness; Mathematics; Artificial intelligence; Pattern recognition (psychology); Computer vision; Computer science","score_opus":0.08235764575415004,"score_gpt":0.2935960342998326,"score_spread":0.21123838854568255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2895228715","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9691867,0.0010818845,0.0045747417,0.00047878484,0.00064056186,0.00011230396,0.000005396153,0.00007907309,0.02384056],"genre_scores_gemma":[0.9964246,0.00003627143,0.00014392562,0.00020874602,0.0001189192,0.000012986151,0.000015027394,0.00001019644,0.0030292866],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9993673,0.000043857526,0.00010917006,0.00024502413,0.000068103094,0.00016657067],"domain_scores_gemma":[0.999564,0.00001940403,0.00003362462,0.00013722466,0.00011115678,0.00013458835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00012532869,0.00010245871,0.000117762276,0.00005679205,0.00008945909,0.0001076364,0.00007074689,0.000040021285,0.00051421946],"category_scores_gemma":[0.000029712464,0.00009334112,0.000011625224,0.00007819375,0.00016299057,0.0001515464,0.00003403078,0.000066676024,0.000043542084],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024562745,0.0002901309,0.57142544,0.0001043046,0.00008797611,0.00011804221,0.14624605,0.000007188279,0.0142124165,0.13467892,0.059094608,0.0734893],"study_design_scores_gemma":[0.0023710087,0.00017208906,0.921495,0.00004484197,0.00007403389,0.00029385288,0.020892236,0.0031134828,0.0002685398,0.0017582022,0.048930485,0.000586213],"about_ca_topic_score_codex":0.0003700158,"about_ca_topic_score_gemma":0.00007199152,"teacher_disagreement_score":0.35006958,"about_ca_system_score_codex":0.00001590689,"about_ca_system_score_gemma":0.000045195695,"threshold_uncertainty_score":0.56303424},"labels":[],"label_agreement":null},{"id":"W2897104541","doi":"10.2352/cic.2014.22.1.art00012","title":"Subspace-Clustering-Based Multispectral Image Compression","year":2014,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Multispectral image; Lossless compression; Linear subspace; Data compression; Redundancy (engineering); Hyperspectral imaging; Image compression; JPEG 2000; Cluster analysis; Computer science; Artificial intelligence; Multispectral pattern recognition; Subspace topology; Dimension (graph theory); Pattern recognition (psychology); Compression (physics); Mathematics; Computer vision; Algorithm; Image processing; Image (mathematics); Physics; Combinatorics; Geometry","score_opus":0.010614231518210828,"score_gpt":0.259756510927532,"score_spread":0.24914227940932115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897104541","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0040136357,0.00006790118,0.9921439,0.0009887264,0.00015815212,0.00015538438,0.0000045677825,0.0006170178,0.0018506711],"genre_scores_gemma":[0.7751466,0.000007768545,0.22432499,0.00041562712,0.000022172248,0.000019247447,0.0000049327027,0.000008988795,0.000049705635],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99874747,0.00009269034,0.00018192234,0.00051129144,0.00015649041,0.00031016304],"domain_scores_gemma":[0.9988396,0.00015582365,0.00009816841,0.00064576155,0.00011688486,0.00014372253],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017777769,0.0001972051,0.00020717768,0.00010027916,0.0001970148,0.00032893513,0.000779287,0.000034503926,0.000024011657],"category_scores_gemma":[0.00009497134,0.00016935763,0.000032591346,0.00012487535,0.00016335929,0.0008024126,0.00056148344,0.0001739022,0.000016710135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006835011,0.00019920287,0.0056202323,0.0001546746,0.00001078767,0.000040554518,0.0006964227,0.00018134416,0.5631336,0.055361815,0.008114864,0.36641818],"study_design_scores_gemma":[0.0004261972,0.000052736617,0.0040565296,0.00010561398,0.000002340334,0.000012683204,0.000010464329,0.944078,0.0420209,0.00247207,0.0065154876,0.0002469582],"about_ca_topic_score_codex":0.000027086187,"about_ca_topic_score_gemma":0.000012940957,"teacher_disagreement_score":0.94389665,"about_ca_system_score_codex":0.00002094844,"about_ca_system_score_gemma":0.000039075803,"threshold_uncertainty_score":0.6906204},"labels":[],"label_agreement":null},{"id":"W2897863306","doi":"10.2352/cic.2014.22.1.art00037","title":"Gaussian Illuminants and Reflectances for Colour Signal Prediction","year":2014,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Studies; University of British Columbia","funders":"","keywords":"Standard illuminant; Chromatic adaptation; Gaussian; Artificial intelligence; Reflectivity; Chromatic scale; Mathematics; Color constancy; Spurious relationship; Computer science; Pattern recognition (psychology); Computer vision; Optics; Image (mathematics); Physics; Statistics","score_opus":0.012360836258558855,"score_gpt":0.2666661877016878,"score_spread":0.25430535144312894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897863306","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8680441,0.00004673333,0.11693437,0.0017294938,0.00007980176,0.00032694926,0.00004339662,0.000033391992,0.0127618015],"genre_scores_gemma":[0.9987704,0.00000431293,0.000700247,0.000074073745,0.000086997854,0.00009373565,0.000007305588,0.0000032989751,0.00025960596],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995241,0.000010130711,0.00008463798,0.00019908583,0.000043788266,0.0001382502],"domain_scores_gemma":[0.99972576,0.00005549527,0.000040606537,0.000068226735,0.00005210911,0.000057793335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010411245,0.00006750582,0.00008367323,0.00002223585,0.00024876863,0.00009586906,0.00006455498,0.000014084936,0.000032841315],"category_scores_gemma":[0.000005636861,0.000059631555,0.000014128844,0.0000549438,0.00013083003,0.00013608146,0.000025153646,0.00005280222,0.0000022939696],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036111192,0.000073636395,0.21094915,0.00003014605,0.000016004175,1.6748368e-7,0.0010031894,0.0000048684683,0.041435562,0.24292314,0.002004357,0.5015237],"study_design_scores_gemma":[0.0020235053,0.000484725,0.25283346,0.00012060277,0.00010135892,0.000007188385,0.002524571,0.47884342,0.011348725,0.10939504,0.1416673,0.00065008155],"about_ca_topic_score_codex":0.00002654069,"about_ca_topic_score_gemma":0.0000065582435,"teacher_disagreement_score":0.50087357,"about_ca_system_score_codex":0.0000040756586,"about_ca_system_score_gemma":0.000031539934,"threshold_uncertainty_score":0.24317043},"labels":[],"label_agreement":null},{"id":"W2909240331","doi":"10.2352/issn.2169-2629.2018.26.225","title":"Colour Image Gradient Regression Reintegration","year":2018,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Engineering and Physical Sciences Research Council","keywords":"Image (mathematics); Regression; Artificial intelligence; Computer science; Computer vision; Statistics; Mathematics","score_opus":0.015606484352157,"score_gpt":0.2916493470120572,"score_spread":0.2760428626599002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909240331","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019961052,0.00014931783,0.96481705,0.003599958,0.0005051798,0.00013606763,0.0000011770442,0.00020960603,0.010620624],"genre_scores_gemma":[0.9076701,0.00005379252,0.09087505,0.00081691035,0.00006700885,0.000008438401,0.0000018444329,0.000006561123,0.0005002932],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989439,0.000047714733,0.00017177589,0.00042410902,0.00015389187,0.00025858716],"domain_scores_gemma":[0.9991132,0.000042807264,0.00008563588,0.00034073024,0.000299231,0.000118382355],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017449236,0.00014407038,0.00013586575,0.000092427494,0.00031219173,0.00036033726,0.00037349563,0.00002175892,0.000038839702],"category_scores_gemma":[0.00011161064,0.000113241236,0.00002639683,0.00019721166,0.0002470128,0.0010226386,0.00025341733,0.000121954115,0.00006630976],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031298503,0.000057562513,0.0020716628,0.000021216965,0.0000064104147,0.00003310973,0.002239999,3.9000076e-7,0.13839756,0.10447773,0.00908268,0.7435804],"study_design_scores_gemma":[0.0006790247,0.00020696377,0.009549485,0.0002315266,0.000006661609,0.00009329951,0.00030662134,0.9075608,0.032564808,0.01758599,0.030807963,0.00040683395],"about_ca_topic_score_codex":0.00001357011,"about_ca_topic_score_gemma":0.0000049415553,"teacher_disagreement_score":0.9075604,"about_ca_system_score_codex":0.000028353235,"about_ca_system_score_gemma":0.000059913495,"threshold_uncertainty_score":0.46178436},"labels":[],"label_agreement":null},{"id":"W2964100365","doi":"10.2352/issn.2169-2629.2018.26.350","title":"Rehabilitating the ColorChecker Dataset for Illuminant Estimation","year":2018,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Engineering and Physical Sciences Research Council","keywords":"Standard illuminant; Benchmark (surveying); Ground truth; Set (abstract data type); Computer science; Range (aeronautics); Estimation; Artificial intelligence; Algorithm; Machine learning; Data mining; Geography","score_opus":0.01873737524303075,"score_gpt":0.32004963359533706,"score_spread":0.3013122583523063,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2964100365","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71028847,0.000025525356,0.2757222,0.008417731,0.00016189677,0.00092847465,0.00068332895,0.000030031171,0.0037423754],"genre_scores_gemma":[0.9946982,4.435885e-7,0.0046164314,0.00016790164,0.000091452916,0.00018082024,0.00011775145,0.0000033277886,0.00012365927],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995059,0.000013244005,0.00010374576,0.00018199388,0.000050281542,0.00014485665],"domain_scores_gemma":[0.99945915,0.00017789185,0.000049495644,0.00017308684,0.000107278065,0.000033097167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002156603,0.00006356796,0.00006370222,0.000014417982,0.00046918064,0.000111632806,0.00014545686,0.000006898303,0.00007111861],"category_scores_gemma":[0.000038479076,0.000044422424,0.000016732478,0.000085039916,0.00039168136,0.00014836995,0.000058189296,0.000041454015,0.000017468714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003431149,0.00010249287,0.032167025,0.000025763522,0.000020183332,1.5519977e-7,0.0043763733,0.000015165985,0.014681793,0.4320136,0.034706056,0.4818571],"study_design_scores_gemma":[0.00055869954,0.00018525797,0.028458582,0.000041322302,0.000051914856,0.0000021751116,0.004673834,0.6765709,0.0041429996,0.04894348,0.23605698,0.00031386036],"about_ca_topic_score_codex":0.00008347935,"about_ca_topic_score_gemma":0.0000110508045,"teacher_disagreement_score":0.67655575,"about_ca_system_score_codex":0.000005745577,"about_ca_system_score_gemma":0.000051521125,"threshold_uncertainty_score":0.36086056},"labels":[],"label_agreement":null},{"id":"W3023527190","doi":"10.2352/cic.2004.12.1.art00010","title":"Estimating Illumination Chromaticity via Support Vector Regression","year":2004,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":88,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Chromaticity; Artificial intelligence; Computer vision; Color histogram; Color balance; Computer science; Histogram; Color constancy; Support vector machine; Color normalization; Pattern recognition (psychology); Color image; Color correction; Artificial neural network; Image (mathematics); Image processing","score_opus":0.011938320095176416,"score_gpt":0.27679346514995035,"score_spread":0.2648551450547739,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3023527190","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.74504006,0.000007031507,0.24894613,0.0013893314,0.000090929985,0.00014470603,0.00000558574,0.000040132825,0.0043361024],"genre_scores_gemma":[0.9936411,4.0317585e-7,0.0061040283,0.000055593577,0.00006988771,0.000034885772,0.000014265862,0.000004155168,0.00007569482],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994377,0.000008170665,0.00012295533,0.00019314767,0.00008914518,0.00014887532],"domain_scores_gemma":[0.9996592,0.000021572105,0.00007157914,0.000117092204,0.00006818969,0.00006238667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000085355525,0.00008597565,0.00009170796,0.000029129757,0.00024588872,0.00009317087,0.00010261491,0.000010718189,0.00014856044],"category_scores_gemma":[0.000009340501,0.00007445845,0.000021199245,0.00010808739,0.00010856278,0.00024384724,0.000050716946,0.00006642629,0.000032116594],"study_design_candidate":"design_other","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011782558,0.00035417243,0.047295656,0.000057396377,0.000021620053,0.0000051498996,0.004266498,0.00036044992,0.16486691,0.16642706,0.0005912621,0.615742],"study_design_scores_gemma":[0.0020388747,0.00020561756,0.20165895,0.00037055917,0.00008750887,0.00002481671,0.0014844778,0.54094267,0.07568228,0.17459929,0.0018832955,0.0010216522],"about_ca_topic_score_codex":0.00010692744,"about_ca_topic_score_gemma":0.0000032727608,"teacher_disagreement_score":0.6147204,"about_ca_system_score_codex":0.000018035675,"about_ca_system_score_gemma":0.00007813319,"threshold_uncertainty_score":0.30363274},"labels":[],"label_agreement":null},{"id":"W42537546","doi":"10.2352/cic.2004.12.1.art00017","title":"Analysis of Spatio-chromatic Decorrelation for Colour Image Reconstruction","year":2004,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Decorrelation; Chromatic scale; Computer science; Artificial intelligence; Computer vision; Encoding (memory); Basis (linear algebra); Discrete cosine transform; Data compression; Iterative reconstruction; Spatial analysis; Human visual system model; Image compression; Pattern recognition (psychology); Perception; Image (mathematics); Mathematics; Image processing","score_opus":0.013796081988299926,"score_gpt":0.27078879868578387,"score_spread":0.25699271669748397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W42537546","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26599705,0.000010943721,0.7326381,0.0007006674,0.00004838851,0.00016147546,0.0000041936955,0.00007586214,0.00036329814],"genre_scores_gemma":[0.82146543,0.000007998472,0.17838815,0.000084622465,0.000004056012,0.000023459259,0.000010339582,0.0000025607387,0.0000133583735],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993722,0.000029434183,0.00021952445,0.00020199991,0.000083135885,0.00009370869],"domain_scores_gemma":[0.9992914,0.00008826425,0.0001635593,0.00017984911,0.00024412991,0.000032799926],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023875156,0.00007334349,0.00016994971,0.0002564096,0.00007613236,0.000121126664,0.00015755926,0.000024592217,0.000007797437],"category_scores_gemma":[0.00008842568,0.00007431754,0.000051652805,0.00040105777,0.00007381619,0.00058993715,0.000039645638,0.00004448042,0.0000013806426],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004525108,0.00018433575,0.03582701,0.00014429523,0.00038810095,0.0000027723256,0.008941549,0.0017946347,0.04655029,0.62762785,0.00023332439,0.2782606],"study_design_scores_gemma":[0.0004180284,0.00008342582,0.049965028,0.000033142103,0.0001415123,0.000009416234,0.00009070717,0.9173613,0.007955172,0.023709586,0.000088017165,0.0001446563],"about_ca_topic_score_codex":0.00003311454,"about_ca_topic_score_gemma":0.000043867338,"teacher_disagreement_score":0.9155667,"about_ca_system_score_codex":0.000029688004,"about_ca_system_score_gemma":0.00009338406,"threshold_uncertainty_score":0.30305812},"labels":[],"label_agreement":null},{"id":"W4319599285","doi":"10.2352/cic.2022.30.1.23","title":"A 360° Omnidirectional Photometer using a Ricoh Theta Z1","year":2022,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"Luminance; Photometer; Omnidirectional antenna; Computer vision; Computer science; Calibration; Optics; Artificial intelligence; Computer graphics (images); Metre; Remote sensing; Physics; Geography; Telecommunications","score_opus":0.0383423169572753,"score_gpt":0.2800574390001231,"score_spread":0.24171512204284779,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319599285","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16181622,0.00032265126,0.82846725,0.00077377015,0.0005092236,0.00028251827,0.000009237311,0.0004536983,0.0073654135],"genre_scores_gemma":[0.9484537,0.000014528258,0.04974042,0.0007324085,0.00003070729,0.00009276568,0.0000033629399,0.00000974019,0.00092236407],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987014,0.000111588604,0.00016846079,0.00043691936,0.0002974458,0.0002842088],"domain_scores_gemma":[0.9993459,0.0000627695,0.000084066065,0.00034455335,0.0001023481,0.000060373262],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034948267,0.00014621216,0.00014920528,0.00017631377,0.00048095643,0.0003096736,0.0005790259,0.000014414234,0.00026963148],"category_scores_gemma":[0.00003066025,0.00015057405,0.000042303327,0.00036560334,0.00009228298,0.0005261524,0.0008594558,0.00020972558,0.000009656774],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013277149,0.00062155543,0.017584916,0.00009732459,0.00011995224,0.00012386752,0.0069792094,0.00009312362,0.75195724,0.051148146,0.013665563,0.15747635],"study_design_scores_gemma":[0.0016940591,0.0002735645,0.0066458555,0.00008203552,0.000051464645,0.00083811866,0.00024098708,0.7330779,0.042696573,0.021414151,0.19159515,0.0013901888],"about_ca_topic_score_codex":0.00008751371,"about_ca_topic_score_gemma":0.0000030725096,"teacher_disagreement_score":0.7866375,"about_ca_system_score_codex":0.0000885295,"about_ca_system_score_gemma":0.00013221262,"threshold_uncertainty_score":0.61402315},"labels":[],"label_agreement":null},{"id":"W4319599294","doi":"10.2352/cic.2022.30.1.32","title":"Laplacian of Logarithm as Illuminant-Invariant Input Space","year":2022,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Standard illuminant; Logarithm; Laplace operator; Artificial intelligence; Invariant (physics); Mathematics; Color constancy; Computer vision; Pixel; Color space; Color balance; Convolutional neural network; Pattern recognition (psychology); Computer science; Color image; Image (mathematics); Image processing; Mathematical analysis","score_opus":0.008717098926293099,"score_gpt":0.24288320294419088,"score_spread":0.23416610401789778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319599294","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9173198,0.00005625695,0.008029253,0.0037760325,0.00011975432,0.00024279862,0.000076367054,0.000026197227,0.07035355],"genre_scores_gemma":[0.9988327,0.0000024916665,0.00026840184,0.00010406456,0.000023906232,0.000058127316,0.000009289501,0.0000038666617,0.0006971283],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994164,0.000022160042,0.00011012098,0.00019320394,0.00010706911,0.00015104408],"domain_scores_gemma":[0.99964243,0.00003526254,0.00007044129,0.00015123624,0.00004735622,0.00005326575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011568884,0.00007178854,0.00010939896,0.000042559233,0.00028411116,0.000038954644,0.00017928286,0.0000056361596,0.0007354363],"category_scores_gemma":[0.0000040267523,0.00007204545,0.000027160866,0.0001680945,0.0001422262,0.000086939435,0.00020111229,0.00010187168,0.000011173817],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022642844,0.00022787253,0.08413628,0.000012960864,0.000021663684,0.0000060517727,0.002429733,0.000048067104,0.028990999,0.7915848,0.0019268161,0.090592116],"study_design_scores_gemma":[0.0031649594,0.000771917,0.09244514,0.00009240801,0.00018724568,0.000074612006,0.042372324,0.13720493,0.041038036,0.12624073,0.55466974,0.0017379518],"about_ca_topic_score_codex":0.0004327141,"about_ca_topic_score_gemma":0.000006122182,"teacher_disagreement_score":0.66534406,"about_ca_system_score_codex":0.00000982424,"about_ca_system_score_gemma":0.00013604797,"threshold_uncertainty_score":0.8052511},"labels":[],"label_agreement":null},{"id":"W4377984119","doi":"10.2352/cic.2000.8.1.art00022","title":"Retinex in Matlab","year":2000,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Optical Polarization and Ellipsometry","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Color constancy; Computer science; MATLAB; Lightness; Computer vision; Artificial intelligence; Computation; Implementation; Pixel; Computer graphics (images); Image (mathematics); Algorithm","score_opus":0.004329788983833215,"score_gpt":0.18439436649808477,"score_spread":0.18006457751425156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377984119","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8471533,0.0003607278,0.0014480178,0.00043297865,0.00008329391,0.000058954487,0.00000239255,0.00016383496,0.15029651],"genre_scores_gemma":[0.9987569,0.00015512697,0.00028934082,0.00013412828,0.000013574868,0.0000021796534,0.0000020393625,0.000006069232,0.0006406631],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996954,0.0000054489146,0.00007808822,0.00007341882,0.000033877277,0.000113758455],"domain_scores_gemma":[0.99987763,0.000013837678,0.000002814359,0.000055471894,0.000009437255,0.000040816263],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000034816607,0.00005276815,0.000064265114,0.000040743693,0.000016425225,0.000042962445,0.000041025116,0.00001802868,0.00061730057],"category_scores_gemma":[0.000010141475,0.00005303957,0.0000064469905,0.00010799757,0.000031198542,0.000083434825,0.000006375358,0.000076578544,0.0001099954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045989604,0.000096926306,0.14862143,0.00028615855,0.000019883677,0.000059398404,0.0016746564,0.0027139825,0.02261284,0.024091596,0.0072234436,0.7925537],"study_design_scores_gemma":[0.00057439686,0.0000161503,0.12967485,0.00006995576,0.0000057704897,0.000012500228,0.00009197489,0.81789684,0.00093334645,0.001349747,0.049064267,0.00031019686],"about_ca_topic_score_codex":0.0000074830195,"about_ca_topic_score_gemma":0.0000026430093,"teacher_disagreement_score":0.81518286,"about_ca_system_score_codex":0.00000807598,"about_ca_system_score_gemma":0.0000049662326,"threshold_uncertainty_score":0.6759008},"labels":[],"label_agreement":null},{"id":"W4377996125","doi":"10.2352/cic.2012.20.1.art00028","title":"Automated Pre–processing Method for Dermoscopic Images and its Application to Pigmented Skin Lesion Segmentation","year":2012,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Cutaneous Melanoma Detection and Management","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Thresholding; Grayscale; Artificial intelligence; Segmentation; Computer science; Computer vision; Image processing; Image segmentation; Pattern recognition (psychology); Simple (philosophy); Image (mathematics)","score_opus":0.029147657975425158,"score_gpt":0.35981601158298,"score_spread":0.3306683536075548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377996125","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3772222,0.0003806805,0.6196427,0.001007147,0.0000821391,0.0011516988,0.0000046458445,0.00019639933,0.0003124141],"genre_scores_gemma":[0.96117955,0.000047849087,0.03743224,0.00050637603,0.00004885593,0.00019418757,0.000028679126,0.000012247957,0.0005500174],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933213,0.000025810987,0.00014499565,0.0002150756,0.000086838074,0.00019513226],"domain_scores_gemma":[0.9995661,0.00003764577,0.000060827628,0.000082517465,0.000114070026,0.00013885194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018742117,0.000107360276,0.00014044916,0.000092985545,0.00013734234,0.000059769405,0.00002805047,0.000026095642,0.000013614104],"category_scores_gemma":[0.000050702532,0.000099273995,0.000014111418,0.0000888632,0.00001737073,0.00014676581,0.000040582512,0.000043560223,0.000007267848],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012244357,0.00005602366,0.0018810411,0.00031726118,0.000014449215,4.1876245e-7,0.000845437,0.000003909566,0.70362115,0.00011646207,0.0004807192,0.29254067],"study_design_scores_gemma":[0.0039805034,0.00045840704,0.16700605,0.0004985378,0.00052954996,0.00035107436,0.0017621903,0.513473,0.26471663,0.00014751556,0.046427783,0.0006488072],"about_ca_topic_score_codex":0.000022283913,"about_ca_topic_score_gemma":0.000005636946,"teacher_disagreement_score":0.5839573,"about_ca_system_score_codex":0.00004311917,"about_ca_system_score_gemma":0.00002251474,"threshold_uncertainty_score":0.40482762},"labels":[],"label_agreement":null},{"id":"W4377997021","doi":"10.2352/cic.2001.9.1.art00063","title":"DLP Cinema™ Technology: Color Management and Signal Processing","year":2001,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Computer Graphics and Visualization Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Movie theater; Color management; Projection (relational algebra); Computer science; Computer graphics (images); Digital Light Processing; Computer vision; Art; Art history; Color space","score_opus":0.021626730897861674,"score_gpt":0.28647684187952105,"score_spread":0.2648501109816594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377997021","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045498233,0.00073908595,0.94969773,0.0015881235,0.00004850942,0.00021851485,7.411713e-7,0.00049389177,0.0017151745],"genre_scores_gemma":[0.9578146,0.00044345143,0.04095784,0.00046042755,0.000018217437,0.00003639061,0.0000018132542,0.000007737908,0.00025956184],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989458,0.000022069195,0.00018823554,0.00045892713,0.0001375537,0.00024742514],"domain_scores_gemma":[0.99942565,0.000022241755,0.0000784433,0.00023631935,0.00015814531,0.00007921323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017154071,0.0001588733,0.00016437875,0.0003245854,0.00025649893,0.00050002313,0.00040891964,0.000043629916,0.000009681512],"category_scores_gemma":[0.0000061616183,0.0001511829,0.000017988024,0.00057738496,0.00017083743,0.00037672254,0.0005310334,0.00011073419,0.0000025974896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000072692883,0.00005958888,0.022599675,0.00007616345,0.000012877365,0.00003107656,0.00040061577,7.922746e-7,0.000832555,0.5076007,0.00061273837,0.46776596],"study_design_scores_gemma":[0.0008950477,0.00019686072,0.020165335,0.00034935717,0.000032531094,0.00029131622,0.0001923961,0.78572077,0.0010557998,0.07758323,0.112774335,0.00074303895],"about_ca_topic_score_codex":0.000007092417,"about_ca_topic_score_gemma":0.0000047153776,"teacher_disagreement_score":0.9123163,"about_ca_system_score_codex":0.000012342817,"about_ca_system_score_gemma":0.00003494119,"threshold_uncertainty_score":0.616506},"labels":[],"label_agreement":null},{"id":"W4392855014","doi":"10.2352/cic.2023.31.1.22","title":"First-principles Approach to Image Lightness Processing","year":2023,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canada First Research Excellence Fund; Engineering and Physical Sciences Research Council; York University","keywords":"Lightness; Computer science; Image (mathematics); Computer vision; Artificial intelligence; Image processing; Computer graphics (images)","score_opus":0.0328667275693564,"score_gpt":0.2826594576007438,"score_spread":0.24979273003138738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392855014","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.78570503,0.000028143153,0.108218715,0.0054462445,0.000075617456,0.00045337234,0.000023360542,0.00022624838,0.09982329],"genre_scores_gemma":[0.99671686,0.0000020506163,0.0020550506,0.000075858356,0.00006559799,0.00016413591,0.000011339371,0.000006801687,0.0009023029],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927336,0.000006784236,0.00010618875,0.00029150874,0.00008744412,0.00023472194],"domain_scores_gemma":[0.99961406,0.000025071484,0.000031951182,0.00014652501,0.00008155753,0.00010080944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00010355506,0.00009482666,0.00010027304,0.000065949775,0.00034833216,0.00026233585,0.00020055476,0.000008972463,0.00003612767],"category_scores_gemma":[0.000007551307,0.000085673666,0.00002106705,0.00043655882,0.00008817146,0.00020409141,0.00014989407,0.00006189075,0.00010983038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000027211785,0.0004237224,0.1271929,0.00022116414,0.000031797066,0.0000054238776,0.012546047,0.0016411617,0.043270625,0.56914204,0.0109707685,0.23452713],"study_design_scores_gemma":[0.0004102748,0.00002684635,0.1389138,0.00009260382,0.00002722852,0.0000032179685,0.005072134,0.78029245,0.003986428,0.009211627,0.061358444,0.00060494005],"about_ca_topic_score_codex":0.000042303687,"about_ca_topic_score_gemma":0.000002170246,"teacher_disagreement_score":0.7786513,"about_ca_system_score_codex":0.0000065894405,"about_ca_system_score_gemma":0.00006121768,"threshold_uncertainty_score":0.34936708},"labels":[],"label_agreement":null},{"id":"W4392855056","doi":"10.2352/cic.2023.31.1.17","title":"What Underlies Focal Colours?","year":2023,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","score_opus":0.023414071728992448,"score_gpt":0.29504443285926346,"score_spread":0.271630361130271,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392855056","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97414774,0.00006525793,0.004736154,0.008147003,0.00027405782,0.00017340756,0.00000971134,0.000121761834,0.01232492],"genre_scores_gemma":[0.9981333,0.000031823274,0.00006449887,0.00012924775,0.00005347565,0.000050314902,0.000012093135,0.000004003817,0.0015212296],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994627,0.000009417292,0.00007723728,0.00018996153,0.000069850656,0.00019078488],"domain_scores_gemma":[0.9996936,0.00005829628,0.000025260548,0.000115302246,0.000044873846,0.00006272082],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000077946584,0.00007136031,0.00007971146,0.000040639872,0.00021025974,0.0003380352,0.00012248677,0.000008992661,0.00016458383],"category_scores_gemma":[0.0000035371745,0.00006588222,0.00002230125,0.00022317274,0.00014951744,0.0003636805,0.00008470078,0.00006038863,0.00015886687],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000008061581,0.000063293024,0.09721274,0.000011502969,0.000020315887,0.0000034884395,0.002004292,0.00002603709,0.008032696,0.49564427,0.012891053,0.38408223],"study_design_scores_gemma":[0.0013129459,0.0001319088,0.28329438,0.00016720529,0.00007412491,0.0000074756326,0.05179183,0.19560444,0.0056762137,0.29222015,0.16863172,0.0010876015],"about_ca_topic_score_codex":0.000033502107,"about_ca_topic_score_gemma":0.0000061003075,"teacher_disagreement_score":0.38299465,"about_ca_system_score_codex":0.000005126876,"about_ca_system_score_gemma":0.000056142788,"threshold_uncertainty_score":0.32596812},"labels":[],"label_agreement":null},{"id":"W4392855074","doi":"10.2352/cic.2023.31.1.21","title":"Simplifying Tone Curves for Image Enhancement","year":2023,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Canada First Research Excellence Fund; Engineering and Physical Sciences Research Council; York University","keywords":"Tone (literature); Tone mapping; Image (mathematics); Mathematics; Computer science; Computer vision; Art; Literature","score_opus":0.0472825974380164,"score_gpt":0.3567797999355005,"score_spread":0.30949720249748414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392855074","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0058527053,0.0006157293,0.9867827,0.003962334,0.00029237047,0.0002532099,0.0000037555726,0.00022838954,0.0020087915],"genre_scores_gemma":[0.77642965,0.0008842915,0.21585351,0.0036946263,0.00011130385,0.00017611163,0.00001747555,0.000021729697,0.0028112791],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989384,0.000052561823,0.00016884741,0.0003674611,0.00013726672,0.00033548137],"domain_scores_gemma":[0.9991837,0.0002606251,0.00005212379,0.00026095452,0.00016725453,0.00007533079],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006242196,0.00012352777,0.00016882796,0.000090230555,0.00021959793,0.0003253622,0.0003876275,0.000017531302,0.000014331682],"category_scores_gemma":[0.00017578006,0.00011578602,0.000040485316,0.0002704673,0.000075707685,0.00050260825,0.00024380503,0.00007160472,0.00003429962],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032491935,0.00004912131,0.00029513775,0.00059517875,0.000027527904,0.00006478642,0.0014013841,0.000003540365,0.4536052,0.02873753,0.034882817,0.48030525],"study_design_scores_gemma":[0.0024480596,0.0002926807,0.005497705,0.00084441033,0.000051334813,0.00006407308,0.00022767796,0.7277187,0.1721179,0.04753861,0.04214421,0.0010546274],"about_ca_topic_score_codex":0.000010199879,"about_ca_topic_score_gemma":7.013226e-7,"teacher_disagreement_score":0.7709292,"about_ca_system_score_codex":0.00001333999,"about_ca_system_score_gemma":0.00006696827,"threshold_uncertainty_score":0.47216168},"labels":[],"label_agreement":null},{"id":"W4407176389","doi":"10.2352/cic.2024.32.1.10","title":"Neural Image Compression and the Degradation of Color: An Analysis","year":2024,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"Degradation (telecommunications); Artificial intelligence; Compression (physics); Image (mathematics); Computer vision; Computer science; Pattern recognition (psychology); Materials science; Composite material","score_opus":0.020797606370535262,"score_gpt":0.3015490330098544,"score_spread":0.2807514266393192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407176389","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2604687,0.0011552273,0.7363978,0.0012186475,0.000116883886,0.00009026557,0.0000025858392,0.000059572594,0.00049031695],"genre_scores_gemma":[0.9808798,0.000060162856,0.01873845,0.00014710329,0.000014036574,0.0000051630905,0.0000033657755,0.0000034296813,0.00014847972],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990475,0.00025276956,0.00016359564,0.00028378304,0.00013160685,0.000120744975],"domain_scores_gemma":[0.99924624,0.00031527277,0.00004739163,0.00023641328,0.00010579891,0.00004891326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059949287,0.00009438508,0.00019381674,0.00013223907,0.00013481222,0.000641299,0.0002783719,0.000018321809,0.000007581897],"category_scores_gemma":[0.000049568123,0.000060370498,0.000045018307,0.0003765246,0.0003083116,0.00074403244,0.00015987642,0.00010167802,9.141709e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002021571,0.000064006184,0.004950126,0.0001767289,0.00019857663,0.00006656123,0.006104959,0.000113371134,0.19202499,0.19121502,0.00035863835,0.60452485],"study_design_scores_gemma":[0.0003400639,0.00003105824,0.008577382,0.000026039963,0.000110177105,0.000016034117,0.00007925613,0.9848584,0.0032780783,0.0024621412,0.00014123067,0.000080117476],"about_ca_topic_score_codex":0.00011376897,"about_ca_topic_score_gemma":0.000006969923,"teacher_disagreement_score":0.984745,"about_ca_system_score_codex":0.000006269765,"about_ca_system_score_gemma":0.00003609364,"threshold_uncertainty_score":0.61840606},"labels":[],"label_agreement":null},{"id":"W52574610","doi":"10.2352/cic.2000.8.1.art00020","title":"A Composite Spectral Model and Its Applications","year":2000,"lang":"en","type":"article","venue":"Color and Imaging Conference","topic":"Color Science and Applications","field":"Physics and Astronomy","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; Optech (Canada)","funders":"","keywords":"Software portability; Representation (politics); Compact space; Computer science; Flexibility (engineering); Composite number; Algorithm; Fourier transform; Sampling (signal processing); Point (geometry); Image (mathematics); Theoretical computer science; Artificial intelligence; Mathematics; Computer vision; Mathematical analysis; Statistics","score_opus":0.012340395851887795,"score_gpt":0.2575307895976468,"score_spread":0.24519039374575902,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W52574610","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.938212,0.000114069495,0.014966818,0.0011602186,0.000005946189,0.00024230951,0.000028173186,0.00003280646,0.04523766],"genre_scores_gemma":[0.9980727,0.000023516382,0.0006033374,0.000102385195,0.00003213761,0.00009994485,0.000006709445,0.0000032596997,0.0010559991],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995513,0.000004721838,0.000075299016,0.00019376604,0.000042692147,0.00013223522],"domain_scores_gemma":[0.9997719,0.000017164532,0.000017497825,0.00009082957,0.000029306071,0.00007333031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00002999604,0.00006985647,0.000071282244,0.000017726095,0.00020857432,0.00009964384,0.00008693714,0.0000071851264,0.00024772988],"category_scores_gemma":[4.1961403e-7,0.00006733213,0.000013813048,0.00007701222,0.000076789365,0.0001386519,0.000026353324,0.000057662557,0.000032869342],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011891901,0.0001343211,0.0219347,0.000012567517,0.000014635404,4.789207e-7,0.000865453,0.00037639483,0.039483152,0.51210773,0.0003852252,0.42467344],"study_design_scores_gemma":[0.0003323635,0.000014198947,0.015046049,0.000013248953,0.000026026632,0.000004350333,0.00015972319,0.9325876,0.0013569613,0.03832042,0.01188803,0.00025101576],"about_ca_topic_score_codex":0.000020119265,"about_ca_topic_score_gemma":0.0000016739599,"teacher_disagreement_score":0.9322112,"about_ca_system_score_codex":0.0000034039879,"about_ca_system_score_gemma":0.000031037238,"threshold_uncertainty_score":0.27457246},"labels":[],"label_agreement":null}]}