{"meta":{"query_hash":"c2bd9524c072","filters":{"venue":"Advances in computer vision and pattern recognition"},"cohort_total":8,"direct_labels_cover":0,"predictions_cover":8,"exported":8,"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/c2bd9524c072","api":"https://metacan.xera.ac/api/v1/cohort?venue=Advances+in+computer+vision+and+pattern+recognition"},"results":[{"id":"W159272853","doi":"10.1007/978-1-4471-5195-1_29","title":"Detecting, Representing and Attending to Visual Shape","year":2013,"lang":"en","type":"book-chapter","venue":"Advances in computer vision and pattern recognition","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; McGill University","funders":"","keywords":"Artificial intelligence; Computer vision; Computer science; Optometry; Psychology; Computer graphics (images); Cartography; Geography; Medicine","score_opus":0.026626853113853478,"score_gpt":0.309598741131459,"score_spread":0.28297188801760553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W159272853","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":[0.030292729,0.000983646,0.9517454,0.000318868,0.0018764916,0.00076057867,0.0000071250925,0.0002885676,0.013726622],"genre_scores_gemma":[0.84878635,0.009704837,0.10403578,0.0074208644,0.0026240645,0.00021592127,0.00016509475,0.00030251918,0.026744567],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977477,0.00006535481,0.00053510064,0.0010397882,0.00031040612,0.000301648],"domain_scores_gemma":[0.9990514,0.0001596644,0.0002624592,0.00024835003,0.00010727929,0.00017087637],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000301199,0.00037087325,0.00036882632,0.0005436366,0.00018852651,0.00040904948,0.0002304196,0.00020717339,0.0001299846],"category_scores_gemma":[0.000016898794,0.00036311997,0.000076031145,0.000112309295,0.000044188015,0.0011382406,0.0005608863,0.00038867068,0.00022131074],"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":[0.000005692955,0.000015543768,0.00016646957,0.00008285285,0.0000066671405,0.000019337816,0.00013099666,0.0000085295815,0.000050430048,0.00020618319,0.000048514008,0.99925876],"study_design_scores_gemma":[0.0020871894,0.0028068533,0.005965172,0.006919832,0.000051085404,0.0006456813,0.000054923235,0.8536246,0.00048202343,0.067995116,0.05637075,0.0029967835],"about_ca_topic_score_codex":0.000012824437,"about_ca_topic_score_gemma":0.000038184502,"teacher_disagreement_score":0.996262,"about_ca_system_score_codex":0.000041717318,"about_ca_system_score_gemma":0.000008481552,"threshold_uncertainty_score":0.9998821},"labels":[],"label_agreement":null},{"id":"W1633411078","doi":"10.1007/978-1-84800-304-0_10","title":"Towards OpenVL: Improving Real-Time Performance of Computer Vision Applications","year":2008,"lang":"en","type":"book-chapter","venue":"Advances in computer vision and pattern recognition","topic":"CCD and CMOS Imaging Sensors","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Scalability; Implementation; Software; Pipeline (software); Synchronization (alternating current); Middleware (distributed applications); Distributed computing; Embedded system; Reusability; Real-time computing; Computer architecture; Software engineering; Operating system","score_opus":0.009718912969180501,"score_gpt":0.23527510959201434,"score_spread":0.22555619662283383,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1633411078","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":[0.16402352,0.010307148,0.65907323,0.00012598687,0.0035864902,0.0038895912,0.00063443056,0.0015928467,0.15676677],"genre_scores_gemma":[0.52960944,0.317827,0.13582467,0.00085085625,0.0044437977,0.00021617326,0.003366015,0.0008643273,0.006997726],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99856627,0.000017517526,0.00054637546,0.00043474062,0.00022445334,0.0002106307],"domain_scores_gemma":[0.9993228,0.00008182691,0.00016764042,0.00027000243,0.000086716434,0.00007104507],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009851069,0.00036965054,0.00046612657,0.0002691817,0.00006953518,0.000041920568,0.00016439453,0.00019366757,0.00007988117],"category_scores_gemma":[8.089914e-7,0.00037079517,0.00009083886,0.00006000184,0.000090707996,0.00042804604,0.00011548094,0.0003194923,0.00009296273],"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":[0.000014451221,0.000019651277,0.000036155983,0.0004673339,0.000012615626,0.000010332684,0.00007706709,0.0014441028,0.00012072369,0.000004735888,0.00025214528,0.9975407],"study_design_scores_gemma":[0.0013489722,0.0008635216,0.0017099419,0.0044022333,0.000061334205,0.00022678508,0.0000041790286,0.9116669,0.00065869064,0.00071876426,0.07691975,0.0014188968],"about_ca_topic_score_codex":0.000010839629,"about_ca_topic_score_gemma":0.000007716628,"teacher_disagreement_score":0.99612176,"about_ca_system_score_codex":0.000051038256,"about_ca_system_score_gemma":0.00001287623,"threshold_uncertainty_score":0.9998744},"labels":[],"label_agreement":null},{"id":"W2180876289","doi":"10.1007/978-1-4471-6741-9_1","title":"Industrial Inspection with Open Eyes: Advance with Machine Vision Technology","year":2015,"lang":"en","type":"book-chapter","venue":"Advances in computer vision and pattern recognition","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Machine vision; Computer vision; Artificial intelligence; Computer science; Manufacturing engineering; Engineering; Engineering drawing","score_opus":0.032762735928974204,"score_gpt":0.2727255303335905,"score_spread":0.23996279440461626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2180876289","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":[0.033657514,0.01989645,0.67606556,0.00043618513,0.012962356,0.011240604,0.0007594033,0.0043893955,0.24059254],"genre_scores_gemma":[0.9595841,0.012799314,0.0137515515,0.00043896804,0.0047207517,0.00038030735,0.0015852357,0.000980837,0.0057589347],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99812555,0.000042879547,0.00054650434,0.00066401344,0.00035747775,0.00026355364],"domain_scores_gemma":[0.99905974,0.00006526449,0.0002672129,0.00032118332,0.00017392615,0.00011268324],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00027423448,0.0005352702,0.0006697939,0.00067347154,0.00012238955,0.00018739008,0.0002187047,0.00068469363,0.000066736306],"category_scores_gemma":[0.000005535661,0.00041686025,0.000040287177,0.000219763,0.00009735978,0.00097589585,0.00014837093,0.0009475506,0.000057549125],"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":[0.00036900147,0.00002423532,0.00011030644,0.00008276463,0.000030911237,0.0000633503,0.00003890414,0.0014550264,0.000009040222,0.000055577973,0.00044808624,0.9973128],"study_design_scores_gemma":[0.015565831,0.012342638,0.000102822174,0.016716244,0.00015255735,0.0012472833,0.00009468604,0.046692807,0.00024067562,0.010021523,0.89383256,0.0029903394],"about_ca_topic_score_codex":0.000032002754,"about_ca_topic_score_gemma":0.00049784983,"teacher_disagreement_score":0.9943225,"about_ca_system_score_codex":0.00018281025,"about_ca_system_score_gemma":0.000031307965,"threshold_uncertainty_score":0.99982834},"labels":[],"label_agreement":null},{"id":"W2201441489","doi":"10.1007/978-1-4471-6741-9_2","title":"Infrared Vision: Visual Inspection Beyond the Visible Spectrum","year":2015,"lang":"en","type":"book-chapter","venue":"Advances in computer vision and pattern recognition","topic":"Thermography and Photoacoustic Techniques","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"National Research Council Canada; Université Laval","funders":"","keywords":"Infrared; Nondestructive testing; Thermography; Optics; Materials science; Electromagnetic spectrum; Holography; Optoelectronics; Physics","score_opus":0.013365009999626316,"score_gpt":0.25820115907920865,"score_spread":0.24483614907958234,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2201441489","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":[0.003815901,0.027669568,0.6493367,0.00022019526,0.007004741,0.0021399532,0.00089452334,0.0028908767,0.30602756],"genre_scores_gemma":[0.87623096,0.09315305,0.006439038,0.0025395127,0.0067682858,0.0002783737,0.0027280624,0.00082920754,0.011033523],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99870545,0.000035898753,0.00040629215,0.00037626215,0.00025973725,0.00021633825],"domain_scores_gemma":[0.99938935,0.00012600544,0.00011280333,0.00023516345,0.00005565789,0.00008103765],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022521954,0.00039301018,0.00033826084,0.00032567748,0.000096107025,0.000101196056,0.00015240454,0.0003041927,0.00017408919],"category_scores_gemma":[0.00000223876,0.00031748074,0.00009710851,0.000093186616,0.000101804246,0.00039947277,0.00008077436,0.00058187253,0.000026250393],"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":[0.00003284349,0.000021102942,0.000018513741,0.00013008429,0.000024457664,0.000024128583,0.00014708526,0.0002955391,0.000017108925,0.00013391743,0.003154445,0.99600077],"study_design_scores_gemma":[0.0014782147,0.001834908,0.0006397216,0.0028579445,0.00011076425,0.00020908647,0.000034601497,0.11072672,0.00043471946,0.5497408,0.3301872,0.0017453062],"about_ca_topic_score_codex":0.000005518525,"about_ca_topic_score_gemma":0.0000648543,"teacher_disagreement_score":0.9942555,"about_ca_system_score_codex":0.00006229342,"about_ca_system_score_gemma":0.0000105494355,"threshold_uncertainty_score":0.9999277},"labels":[],"label_agreement":null},{"id":"W2489522791","doi":"10.1007/978-3-319-25781-5_3","title":"Where the Photos Were Taken: Location Prediction by Learning from Flickr Photos","year":2016,"lang":"en","type":"book-chapter","venue":"Advances in computer vision and pattern recognition","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Estimator; Geography; The Internet; Information retrieval; Artificial intelligence; World Wide Web; Statistics; Mathematics","score_opus":0.017453156870637,"score_gpt":0.261638857860583,"score_spread":0.244185700989946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2489522791","genre_codex":"other","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":[0.010075935,0.039591454,0.2922002,0.004355096,0.011381833,0.0066047874,0.0014169503,0.0009916832,0.633382],"genre_scores_gemma":[0.703545,0.22106425,0.0006596409,0.002591246,0.0054209046,0.00048290708,0.0022372797,0.00017514668,0.06382366],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981184,0.00016019278,0.00056132633,0.00040910472,0.0005138299,0.0002371313],"domain_scores_gemma":[0.99857527,0.00041151713,0.0005263295,0.00016996145,0.00025196612,0.000064930566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046499097,0.00028584176,0.00030563716,0.00016237587,0.00065618596,0.0001596377,0.00017861533,0.00030858943,0.00050869037],"category_scores_gemma":[0.000017175811,0.00020814696,0.00007937479,0.00006645331,0.00024589073,0.000835868,0.000083263,0.00039302727,0.00022991242],"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":[0.00001929705,0.000011243066,0.0013412924,0.000079907724,0.000032419022,0.0000017422828,0.004359189,0.000012830061,0.000005969058,0.00013576674,0.001767923,0.99223244],"study_design_scores_gemma":[0.0007577905,0.00016609735,0.00061102025,0.0033765119,0.000035431323,0.000004189145,0.0011070465,0.0010585156,0.00001362641,0.008163451,0.9842608,0.0004455157],"about_ca_topic_score_codex":0.00036659755,"about_ca_topic_score_gemma":0.0022985437,"teacher_disagreement_score":0.9917869,"about_ca_system_score_codex":0.00008455553,"about_ca_system_score_gemma":0.000027816777,"threshold_uncertainty_score":0.84879863},"labels":[],"label_agreement":null},{"id":"W2503931548","doi":"10.1007/978-1-4471-6741-9","title":"Integrated Imaging and Vision Techniques for Industrial Inspection","year":2015,"lang":"en","type":"book","venue":"Advances in computer vision and pattern recognition","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":270,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia, Okanagan Campus; Kelowna General Hospital; University of British Columbia","funders":"","keywords":"Computer vision; Artificial intelligence; Computer science","score_opus":0.02950227043850592,"score_gpt":0.2887707138581019,"score_spread":0.259268443419596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2503931548","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":[0.014083951,0.012554766,0.9157635,0.00011637629,0.018039389,0.006172276,0.00073284266,0.0033147023,0.0292222],"genre_scores_gemma":[0.80922055,0.057155527,0.04661883,0.0021685727,0.053662952,0.0020539877,0.014449636,0.002498539,0.012171376],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985488,0.00006683914,0.0005374474,0.00045044103,0.00019116828,0.00020530223],"domain_scores_gemma":[0.99932915,0.00014149572,0.00015478043,0.00013355393,0.00015097122,0.00009002895],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00043646808,0.00036827082,0.00045887785,0.00051329593,0.00009360272,0.00016905305,0.00006396037,0.0005065351,0.000008976013],"category_scores_gemma":[0.000017650607,0.00034377296,0.00006449152,0.000115278206,0.000048686594,0.00060002273,0.000052767416,0.00054244616,0.0000079790725],"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":[0.000064555235,0.000010699431,0.000027334094,0.00015806696,0.000008735174,0.0000054370003,0.000057338384,0.00003053581,0.000034008946,0.0000027267106,0.0127660865,0.98683447],"study_design_scores_gemma":[0.0028998842,0.0012307251,0.000036866102,0.0058548977,0.00005458312,0.00015310937,0.00005373632,0.15583175,0.0003078753,0.006089725,0.82647026,0.0010165923],"about_ca_topic_score_codex":0.000018111476,"about_ca_topic_score_gemma":0.000048150796,"teacher_disagreement_score":0.9858179,"about_ca_system_score_codex":0.00022247247,"about_ca_system_score_gemma":0.000029994915,"threshold_uncertainty_score":0.9999014},"labels":[],"label_agreement":null},{"id":"W959165447","doi":"10.1007/978-1-4471-5195-1_3","title":"Flux Graphs for 2D Shape Analysis","year":2013,"lang":"en","type":"book-chapter","venue":"Advances in computer vision and pattern recognition","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Graph; Inscribed figure; Mathematics; Combinatorics; Uniqueness; Computer science; Algorithm; Geometry; Mathematical analysis","score_opus":0.024501404154954793,"score_gpt":0.30537194100209797,"score_spread":0.2808705368471432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W959165447","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000050310562,0.00079974014,0.99264383,0.00011786327,0.00042443688,0.0006478268,0.00004269755,0.00017693566,0.0050963303],"genre_scores_gemma":[0.002514177,0.0082328245,0.97170264,0.005867573,0.00039464797,0.00030414056,0.0015819701,0.000076289194,0.00932574],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980251,0.00004597081,0.00056643155,0.0008062516,0.00032599652,0.00023021906],"domain_scores_gemma":[0.9986759,0.00033444085,0.0003195001,0.000367306,0.00017470124,0.0001281869],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00025056503,0.0003355232,0.0004938308,0.00077257905,0.00007523364,0.00021998331,0.00042018958,0.00022269682,0.0006408869],"category_scores_gemma":[0.000009399838,0.00030667405,0.00020930523,0.00016647605,0.000080301805,0.0010177805,0.00021574229,0.00025059583,0.000096066055],"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":[0.000003923296,0.000020522604,0.000023590104,0.00008884712,0.00005052201,0.000008433143,0.00004940497,0.0000039228607,0.000006160064,0.0004317861,0.0010759139,0.99823695],"study_design_scores_gemma":[0.0018517016,0.0013611955,0.00060023315,0.0018454076,0.00037241532,0.000036051653,0.0000068009363,0.5388092,0.0007160741,0.40124705,0.051271923,0.0018819508],"about_ca_topic_score_codex":0.000006264274,"about_ca_topic_score_gemma":0.000023089262,"teacher_disagreement_score":0.996355,"about_ca_system_score_codex":0.000033520602,"about_ca_system_score_gemma":0.000014481414,"threshold_uncertainty_score":0.99993855},"labels":[],"label_agreement":null},{"id":"W98274135","doi":"10.1007/978-0-85729-046-5_8","title":"Stratified Euclidean Reconstruction","year":2010,"lang":"en","type":"book-chapter","venue":"Advances in computer vision and pattern recognition","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor; University of Waterloo","funders":"","keywords":"Affine transformation; Separable space; Stratification (seeds); Euclidean space; Mathematics; Constraint (computer-aided design); Euclidean geometry; Affine space; Computer science; Algorithm; Artificial intelligence; Geometry; Pure mathematics; Mathematical analysis","score_opus":0.018316867697863257,"score_gpt":0.2766278258456305,"score_spread":0.2583109581477672,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W98274135","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00023412862,0.001044002,0.96029264,0.00024151678,0.0027131739,0.00032868772,0.00001924473,0.0001993719,0.03492721],"genre_scores_gemma":[0.017029388,0.024253186,0.941244,0.004354642,0.0019319413,0.000044787605,0.0003734738,0.00019222309,0.010576358],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978046,0.000045406156,0.0006101498,0.0009623974,0.00029519925,0.00028228346],"domain_scores_gemma":[0.99868494,0.00017735813,0.00038871862,0.00048550978,0.00012541989,0.0001380426],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00022528665,0.00043755764,0.00043048963,0.00041979988,0.00014829318,0.00025920616,0.00038623813,0.00031377628,0.00016574434],"category_scores_gemma":[0.000009930045,0.00042036094,0.00010248585,0.000074998796,0.00012414923,0.0018164935,0.00027393628,0.0009164169,0.00013972115],"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":[0.000007385162,0.000015424344,0.000024707264,0.000048120233,0.000004825957,0.000034289034,0.000054198616,0.000005356928,0.000052227315,0.00081010984,0.000029951247,0.9989134],"study_design_scores_gemma":[0.0024040958,0.0008206663,0.00060792273,0.0047373157,0.00003173146,0.0010715254,0.0000141649925,0.16882451,0.00075563113,0.59836,0.21984996,0.002522444],"about_ca_topic_score_codex":0.0000036270117,"about_ca_topic_score_gemma":0.00007703976,"teacher_disagreement_score":0.99639094,"about_ca_system_score_codex":0.000037611484,"about_ca_system_score_gemma":0.000029673647,"threshold_uncertainty_score":0.9998248},"labels":[],"label_agreement":null}]}