{"meta":{"query_hash":"c5419f06c016","filters":{"venue":"Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT, OTS, BRAIN)"},"cohort_total":11,"direct_labels_cover":0,"predictions_cover":11,"exported":11,"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/c5419f06c016","api":"https://metacan.xera.ac/api/v1/cohort?venue=Biophotonics+Congress%3A+Biomedical+Optics+2020+%28Translational%2C+Microscopy%2C+OCT%2C+OTS%2C+BRAIN%29"},"results":[{"id":"W3016309269","doi":"10.1364/translational.2020.jtu3a.24","title":"Whole-Cell Biophysical Parameters Measured with Multimodal Quantitative-Phase Digital Holographic Microscopy and Flow Assays","year":2020,"lang":"en","type":"article","venue":"Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT, OTS, BRAIN)","topic":"Digital Holography and Microscopy","field":"Physics and Astronomy","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":"Université Laval","funders":"","keywords":"Digital holographic microscopy; Microscopy; Digital holography; Phase imaging; Holography; Refractive index; Materials science; Phase (matter); Optics; Biomedical engineering; Chemistry; Optoelectronics; Physics","score_opus":0.01498876309195356,"score_gpt":0.27058183155643195,"score_spread":0.2555930684644784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016309269","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":[0.9447139,0.0009778565,0.034049325,0.0057872343,0.0006162905,0.0015402746,0.01124964,0.00026118432,0.0008043043],"genre_scores_gemma":[0.9379142,0.000058615,0.056679558,0.0011964114,0.00019092385,0.00008705772,0.00362811,0.00015542872,0.0000897121],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99500954,0.00014328219,0.0010901259,0.0016960474,0.00089049316,0.0011704915],"domain_scores_gemma":[0.9968265,0.00064215367,0.00045648855,0.0005473796,0.00034114567,0.0011863146],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.00029953584,0.0010675346,0.0010828908,0.0002971775,0.0004509552,0.00093229144,0.0007491407,0.00043168437,0.000114590795],"category_scores_gemma":[0.000073954914,0.00096642674,0.0005342221,0.0014846218,0.0030963942,0.000860233,0.000185352,0.00095422455,0.00012365624],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019024191,0.0032238378,0.00720851,0.00029499593,0.00092364365,0.00014969576,0.0010457522,0.00009390781,0.9763519,0.0020712868,0.004394747,0.0023392902],"study_design_scores_gemma":[0.099807695,0.022366367,0.0063765426,0.002065614,0.0025380503,0.00021500974,0.005374989,0.14712735,0.52768743,0.007957816,0.16402134,0.014461802],"about_ca_topic_score_codex":0.000022985318,"about_ca_topic_score_gemma":0.0000029529506,"teacher_disagreement_score":0.4486645,"about_ca_system_score_codex":0.00002524226,"about_ca_system_score_gemma":0.00047168363,"threshold_uncertainty_score":0.9996166},"labels":[],"label_agreement":null},{"id":"W3016394530","doi":"10.1364/translational.2020.tth4b.6","title":"A Novel Portable Fluorophore-free Photonic qPCR for Point-of-Care Applications","year":2020,"lang":"en","type":"article","venue":"Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT, OTS, BRAIN)","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","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":"Jewish General Hospital; McGill University","funders":"","keywords":"Point of care; Photonics; Fluorophore; Materials science; Optoelectronics; Polymerase chain reaction; Transmission (telecommunications); Fluorescence; Computer science; Optics; Chemistry; Physics; Medicine; Telecommunications","score_opus":0.0118697039389192,"score_gpt":0.2848457392692616,"score_spread":0.2729760353303424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016394530","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":[0.17552687,0.024778219,0.7181672,0.039776444,0.0013995479,0.010271755,0.02804775,0.00074569025,0.0012865538],"genre_scores_gemma":[0.5486781,0.0017878349,0.4344368,0.004131394,0.00072502875,0.00036977232,0.0094294995,0.00019097964,0.0002505958],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99647933,0.000048495665,0.0010782847,0.0011891528,0.0005674956,0.0006372307],"domain_scores_gemma":[0.9972387,0.00015931403,0.00048743046,0.00093331764,0.0007172603,0.0004639912],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00031806677,0.0005512677,0.00069805805,0.00013895426,0.00026970057,0.00008383056,0.0009517515,0.0006674029,0.000032223106],"category_scores_gemma":[0.00040549584,0.00053963775,0.0005594275,0.0007553613,0.00085102767,0.000023545634,0.00024737723,0.00030566062,0.000008165269],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003810747,0.00027516848,0.0001008022,0.00031397538,0.0002817135,0.0000045460697,0.00008809858,0.000021880925,0.9906899,0.00048984203,0.0062321755,0.0011208245],"study_design_scores_gemma":[0.002097143,0.00074842136,0.000039536284,0.00008927558,0.0002029986,0.00002408271,0.00017371638,0.0025645844,0.7468143,0.00037792756,0.24623178,0.0006362408],"about_ca_topic_score_codex":0.000012418749,"about_ca_topic_score_gemma":0.000023414048,"teacher_disagreement_score":0.3731512,"about_ca_system_score_codex":0.00003793555,"about_ca_system_score_gemma":0.00065966323,"threshold_uncertainty_score":0.9997055},"labels":[],"label_agreement":null},{"id":"W3016630080","doi":"10.1364/translational.2020.jtu3a.20","title":"Time-domain Fluorescence Diffuse Optical Tomography using a Cuboid","year":2020,"lang":"en","type":"article","venue":"Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT, OTS, BRAIN)","topic":"Optical Imaging and Spectroscopy Techniques","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":"Toronto Metropolitan University","funders":"","keywords":"Cuboid; Fluorescence; Diffuse optical imaging; Object (grammar); Computer science; Voxel; Computer vision; Tomography; Materials science; Artificial intelligence; Optics; Physics; Iterative reconstruction; Mathematics; Geometry","score_opus":0.015978297110315256,"score_gpt":0.2970318715411214,"score_spread":0.28105357443080614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016630080","genre_codex":"empirical","genre_gemma":"methods","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":[0.80318797,0.004016953,0.05728282,0.124099314,0.0014153526,0.0039238194,0.0013803806,0.0021635338,0.0025298696],"genre_scores_gemma":[0.26164076,0.00062974053,0.71842456,0.016089952,0.0011704497,0.00009192285,0.0012560793,0.00035984977,0.00033666042],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9937152,0.00016226155,0.0014856543,0.0015699199,0.0016968978,0.0013700398],"domain_scores_gemma":[0.99590075,0.0005750052,0.0002933208,0.00082169176,0.0004522842,0.0019569292],"candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0006436151,0.0009173596,0.0013411427,0.00039731892,0.00038630865,0.00031120592,0.0007616207,0.0007838348,0.0007169506],"category_scores_gemma":[0.0007136012,0.000863092,0.00067729026,0.0018872656,0.0028792536,0.00031552842,0.00024489666,0.0014497921,0.00025316636],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008187512,0.0012633178,0.0010264921,0.0004358977,0.00035431635,0.00073032023,0.00041465755,0.000007584625,0.9825141,0.0019935868,0.009927402,0.0005135955],"study_design_scores_gemma":[0.018205404,0.004444412,0.0017371128,0.0025911608,0.0015963508,0.0015449543,0.00044199283,0.36369416,0.4819898,0.0031917833,0.11616812,0.0043947534],"about_ca_topic_score_codex":0.000017076223,"about_ca_topic_score_gemma":0.0000014806085,"teacher_disagreement_score":0.66114175,"about_ca_system_score_codex":0.00013814437,"about_ca_system_score_gemma":0.0009650148,"threshold_uncertainty_score":0.99983436},"labels":[],"label_agreement":null},{"id":"W3016734058","doi":"10.1364/translational.2020.jtu3a.36","title":"Improving the Accuracy of Continuous-Wave Hyperspectral Near Infrared Spectroscopy with Spatially-Resolved Measurements and Tikhonov Regularization","year":2020,"lang":"en","type":"article","venue":"Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT, OTS, BRAIN)","topic":"Optical Imaging and Spectroscopy Techniques","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":"Lawson Health Research Institute; Western University","funders":"","keywords":"Tikhonov regularization; Hyperspectral imaging; Regularization (linguistics); Spectroscopy; Infrared; Near-infrared spectroscopy; Artificial intelligence; Mathematics; Computational physics; Pattern recognition (psychology); Optics; Computer science; Physics; Inverse problem; Mathematical analysis","score_opus":0.021241098069431086,"score_gpt":0.2741482247112614,"score_spread":0.2529071266418303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3016734058","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":[0.7282852,0.0044967737,0.15056995,0.10583749,0.0007786324,0.006047693,0.0007246428,0.00084720604,0.0024124286],"genre_scores_gemma":[0.5603033,0.00054140185,0.43184417,0.005598974,0.0004313979,0.00006437519,0.00072740094,0.00019671489,0.00029232126],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9958671,0.00013744482,0.0010770321,0.0009331811,0.0012728539,0.00071241497],"domain_scores_gemma":[0.9971929,0.00047807588,0.00051664445,0.00060088694,0.00060137897,0.00061008456],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006203438,0.00058602233,0.00093318505,0.00014043023,0.00031777128,0.00029659213,0.0003823056,0.00037684353,0.0001569128],"category_scores_gemma":[0.001129019,0.00044031785,0.00020741086,0.0008629472,0.001975021,0.00026954635,0.00012734934,0.0008176394,0.0000103889115],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013041189,0.00035753887,0.0027300993,0.00040189442,0.00036902237,0.00006704734,0.0008155415,0.000010144236,0.99062115,0.0010125693,0.0017302814,0.00058058166],"study_design_scores_gemma":[0.00864505,0.003582271,0.0029174474,0.0008790011,0.00090489327,0.00020229303,0.0003347598,0.09635343,0.8743262,0.0008475198,0.009902393,0.0011047211],"about_ca_topic_score_codex":0.000056996847,"about_ca_topic_score_gemma":0.000007961521,"teacher_disagreement_score":0.28127423,"about_ca_system_score_codex":0.00009045532,"about_ca_system_score_gemma":0.0010802811,"threshold_uncertainty_score":0.99980485},"labels":[],"label_agreement":null},{"id":"W3017164893","doi":"10.1364/translational.2020.jth2a.13","title":"Real Time & 3D Photoacoustic Remote Sensing","year":2020,"lang":"en","type":"article","venue":"Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT, OTS, BRAIN)","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","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":"University of Waterloo","funders":"","keywords":"Photoacoustic imaging in biomedicine; Computer science; Frame rate; Frame (networking); Operator (biology); Real-time computing; Computer vision; Optics; Telecommunications; Physics","score_opus":0.011633122684728254,"score_gpt":0.24643815250253098,"score_spread":0.23480502981780274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3017164893","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":[0.28111225,0.004399614,0.6649265,0.019999703,0.00717965,0.0033845413,0.004954621,0.0046959603,0.009347136],"genre_scores_gemma":[0.3872267,0.0033214889,0.59193224,0.008098656,0.0025080794,0.000021176049,0.0043950835,0.000942047,0.0015545454],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99499315,0.00010888496,0.0013151779,0.0010957145,0.0011611282,0.0013259655],"domain_scores_gemma":[0.9968876,0.00090334937,0.00021365871,0.00065677793,0.00025786925,0.0010807135],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00053560815,0.0008975659,0.0009586878,0.00023881572,0.0003537821,0.00030993315,0.0007278849,0.00064387306,0.00090918184],"category_scores_gemma":[0.000489751,0.0009709627,0.00034030687,0.0011996118,0.00079114875,0.00029111363,0.00012763396,0.0011083699,0.00080338353],"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":[0.00012228332,0.00007048383,0.00001788348,0.0004961398,0.000334336,0.0002175609,0.0008052083,0.0036303767,0.9665969,0.00004700312,0.024425047,0.003236789],"study_design_scores_gemma":[0.0019090865,0.00009052904,0.000055333043,0.0003134666,0.00023041465,0.00016738249,0.00007181762,0.89773583,0.015421797,0.00021575348,0.08261911,0.0011694559],"about_ca_topic_score_codex":0.000058979174,"about_ca_topic_score_gemma":0.00000972593,"teacher_disagreement_score":0.9511751,"about_ca_system_score_codex":0.00018130978,"about_ca_system_score_gemma":0.0005901225,"threshold_uncertainty_score":0.9999746},"labels":[],"label_agreement":null},{"id":"W3026524577","doi":"10.1364/oct.2020.otu2e.3","title":"In-vivo, non-contact, cellular resolution imaging of the human cornea and limbus with a line-scan OCT","year":2020,"lang":"en","type":"article","venue":"Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT, OTS, BRAIN)","topic":"Optical Coherence Tomography Applications","field":"Engineering","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":"University of Waterloo","funders":"","keywords":"Optical coherence tomography; Cornea; Resolution (logic); Optics; In vivo; Preclinical imaging; Image resolution; Materials science; Line (geometry); Biomedical engineering; Physics; Computer science; Medicine; Biology; Artificial intelligence","score_opus":0.008949506443117273,"score_gpt":0.23442229852100288,"score_spread":0.22547279207788562,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026524577","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":[0.9548108,0.0031838398,0.0191955,0.017337108,0.00055799173,0.0022805945,0.0010738471,0.00028227238,0.0012780583],"genre_scores_gemma":[0.9893933,0.00017329858,0.009322195,0.0006706175,0.0001272207,0.00007784954,0.0001206907,0.00008400841,0.000030817275],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972762,0.000060200862,0.0008657359,0.00062718574,0.00061441393,0.0005562825],"domain_scores_gemma":[0.9984759,0.00028140898,0.00018471509,0.00048752734,0.00017074293,0.00039969955],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00028864777,0.0004456984,0.0005157575,0.00018784573,0.0001971324,0.000112670845,0.0005946999,0.00026459037,0.00013638157],"category_scores_gemma":[0.00007273647,0.00038534403,0.00016036262,0.0014912161,0.0009531211,0.00022936397,0.000104708684,0.00069267396,0.000010552683],"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":[0.00009537021,0.00019895565,0.004715207,0.0004560478,0.00014610756,0.000037578517,0.0006796043,0.0011705883,0.9876122,0.0026474618,0.0020585952,0.00018228842],"study_design_scores_gemma":[0.0067966236,0.0006832702,0.013012786,0.0010529159,0.00038116655,0.00006685702,0.00040445648,0.66209525,0.28055444,0.0012790015,0.03175225,0.0019209918],"about_ca_topic_score_codex":0.00005269993,"about_ca_topic_score_gemma":0.000062216495,"teacher_disagreement_score":0.7070578,"about_ca_system_score_codex":0.000058886475,"about_ca_system_score_gemma":0.00022784666,"threshold_uncertainty_score":0.99985987},"labels":[],"label_agreement":null},{"id":"W3026864044","doi":"10.1364/ots.2020.sw4d.4","title":"Hyperspectral Photoacoustic Remote Sensing Microscopy","year":2020,"lang":"en","type":"article","venue":"Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT, OTS, BRAIN)","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","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 Waterloo","funders":"","keywords":"Hyperspectral imaging; Materials science; Microscopy; Optics; Remote sensing; Wavelength; Microscope; Reflection (computer programming); Resolution (logic); Image resolution; Chemical imaging; Photoacoustic imaging in biomedicine; Ranging; Optoelectronics; Geology; Computer science; Physics; Artificial intelligence","score_opus":0.011515349577942873,"score_gpt":0.2483063030730328,"score_spread":0.23679095349508994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026864044","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":[0.3317309,0.010978717,0.60915077,0.026430668,0.00871104,0.0029347148,0.0036926286,0.0032722973,0.0030982627],"genre_scores_gemma":[0.7102473,0.0017477404,0.27551737,0.008778605,0.0015277292,0.000013337236,0.0012540758,0.00055633945,0.00035752656],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9945807,0.00010232242,0.0013630786,0.0012481908,0.0011226668,0.0015830372],"domain_scores_gemma":[0.9969463,0.0007198903,0.0002172925,0.00066061324,0.00027279946,0.0011831084],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00047099325,0.0010223648,0.0010328772,0.0002664166,0.00041598963,0.00039775696,0.00085517066,0.0006659968,0.00045655528],"category_scores_gemma":[0.00046243376,0.0011099102,0.00043463375,0.0013441758,0.0009811304,0.00033642302,0.00012115515,0.0013953515,0.00029168875],"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":[0.00013335785,0.000080114165,0.000028799104,0.0005136161,0.00032920597,0.00031238727,0.00094527256,0.0021814248,0.97875774,0.00011003088,0.014704393,0.0019036849],"study_design_scores_gemma":[0.0026812677,0.00016396027,0.00006984918,0.0003650674,0.00026765448,0.0002634741,0.00034819747,0.8041706,0.14203729,0.00037218092,0.047815755,0.001444702],"about_ca_topic_score_codex":0.00004826791,"about_ca_topic_score_gemma":0.00000945069,"teacher_disagreement_score":0.8367204,"about_ca_system_score_codex":0.00022325969,"about_ca_system_score_gemma":0.00064821576,"threshold_uncertainty_score":0.9991351},"labels":[],"label_agreement":null},{"id":"W3027915378","doi":"10.1364/brain.2020.bth3c.2","title":"Late-Photons Hyperspectral Near-Infrared Spectroscopy Improves the Sensitivity to Cerebral Oxygenation in Adults","year":2020,"lang":"en","type":"article","venue":"Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT, OTS, BRAIN)","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","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":"Lawson Health Research Institute; Western University","funders":"","keywords":"Hyperspectral imaging; Photon; Near-infrared spectroscopy; Multispectral image; Sensitivity (control systems); Spectroscopy; Oxygenation; Monte Carlo method; Infrared; Materials science; Nuclear magnetic resonance; Physics; Optics; Medicine; Remote sensing; Internal medicine; Geology; Mathematics; Astronomy","score_opus":0.011198667766664193,"score_gpt":0.2847292183209892,"score_spread":0.273530550554325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3027915378","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":[0.81674737,0.0006212382,0.0062540397,0.1703112,0.0007140969,0.002811756,0.000598853,0.00056966173,0.001371809],"genre_scores_gemma":[0.7958868,0.0003177372,0.18153784,0.02004282,0.0006489064,0.00014320541,0.000801242,0.00018800475,0.00043345767],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9946186,0.00023264729,0.001232554,0.0014087028,0.001257784,0.001249724],"domain_scores_gemma":[0.9968736,0.00062641717,0.0002448927,0.0007412628,0.00037756236,0.0011362403],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00087853865,0.0007623385,0.0010263954,0.00027455227,0.0003860225,0.00038158233,0.00053075404,0.0005627703,0.00026288236],"category_scores_gemma":[0.0010711187,0.0006367821,0.00040873035,0.0018485847,0.0012019532,0.0002997276,0.00018662435,0.0015071544,0.00015999326],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016655275,0.0006703514,0.0024879507,0.00028798913,0.00018067041,0.00033837307,0.0018724871,0.000039834682,0.9800683,0.0014089901,0.010606781,0.00037269236],"study_design_scores_gemma":[0.011098006,0.0038229057,0.0400107,0.0014231266,0.0004372316,0.00032408192,0.0007910465,0.30959162,0.5876716,0.0019080591,0.040455647,0.002465962],"about_ca_topic_score_codex":0.00016103286,"about_ca_topic_score_gemma":0.0000665933,"teacher_disagreement_score":0.39239675,"about_ca_system_score_codex":0.00025934985,"about_ca_system_score_gemma":0.0010638426,"threshold_uncertainty_score":0.99960834},"labels":[],"label_agreement":null},{"id":"W3027930576","doi":"10.1364/translational.2020.tw1b.3","title":"Localization of epileptic activity based on hemodynamics using an intraoperative hyperspectral imaging system","year":2020,"lang":"en","type":"article","venue":"Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT, OTS, BRAIN)","topic":"Optical Imaging and Spectroscopy Techniques","field":"Medicine","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":"Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Hemodynamics; Hyperspectral imaging; Ictal; Epilepsy; Haemodynamic response; Computer science; Medicine; Artificial intelligence; Neuroscience; Radiology; Cardiology; Psychology","score_opus":0.018483381193860268,"score_gpt":0.3102573234795856,"score_spread":0.29177394228572534,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3027930576","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":[0.4294645,0.00042043134,0.54734504,0.018146856,0.00064090214,0.0018602242,0.00079434994,0.00068922393,0.000638454],"genre_scores_gemma":[0.8876104,0.00005176049,0.10848752,0.0028962006,0.00024399166,0.00002126028,0.0005588561,0.00011715991,0.0000128720985],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99587154,0.0002299101,0.0010040625,0.0010659416,0.0011288989,0.00069962715],"domain_scores_gemma":[0.9973221,0.0003618285,0.0003530332,0.00057825516,0.0005507665,0.0008340193],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005258082,0.00062079186,0.0010302336,0.000310773,0.0002679249,0.00015557975,0.0003782044,0.00039542696,0.00011803861],"category_scores_gemma":[0.00037677883,0.00059350196,0.0003075801,0.0010803103,0.0011650636,0.0003259765,0.000061965526,0.00082993344,0.000014569127],"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":[0.0013527625,0.0015336764,0.0021019487,0.0011629103,0.00019416818,0.00021771804,0.00056855404,0.0027802603,0.9856832,0.0033019835,0.00037258858,0.00073021266],"study_design_scores_gemma":[0.0020532957,0.0009660402,0.00018736834,0.00064685283,0.0002310665,0.000058703656,0.00020430809,0.83813775,0.15657583,0.00006621343,0.00040328345,0.0004693286],"about_ca_topic_score_codex":0.000048312493,"about_ca_topic_score_gemma":0.0000034642164,"teacher_disagreement_score":0.8353574,"about_ca_system_score_codex":0.00033677235,"about_ca_system_score_gemma":0.0010626129,"threshold_uncertainty_score":0.9996516},"labels":[],"label_agreement":null},{"id":"W3028222251","doi":"10.1364/ots.2020.stu4d.3","title":"All-optical Reflection-mode Microscopic Histology of Unstained Human Tissues","year":2020,"lang":"en","type":"article","venue":"Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT, OTS, BRAIN)","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","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 Alberta; University of Waterloo","funders":"","keywords":"Histology; Microscopy; Reflection (computer programming); Materials science; Optical microscope; Optics; Computer science; Scanning electron microscope; Pathology; Physics; Medicine; Composite material","score_opus":0.015989508180144073,"score_gpt":0.2949108725247543,"score_spread":0.27892136434461023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028222251","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":[0.7888367,0.010433531,0.1488,0.03259378,0.0061506233,0.0026884794,0.0026374566,0.0020598215,0.0057995883],"genre_scores_gemma":[0.95808303,0.0005463953,0.037185192,0.0022756176,0.00041773156,0.00004843177,0.0010501904,0.00018600206,0.00020737867],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99605125,0.000085675834,0.0013652364,0.0008258619,0.00072760176,0.00094434735],"domain_scores_gemma":[0.9978752,0.00051940297,0.00022123918,0.00047661518,0.00024412254,0.00066338683],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00030861815,0.00064592087,0.00095575606,0.00024588392,0.00022867494,0.00010224739,0.00071919884,0.00060300296,0.00051459996],"category_scores_gemma":[0.00028882723,0.00069647783,0.00027665353,0.00079895876,0.001200291,0.00021573408,0.00009637646,0.0008437841,0.000077160694],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009691545,0.00018742195,0.00028085714,0.00059984426,0.00035067063,0.0000855552,0.0008048118,0.00073994603,0.98200595,0.0019102122,0.012599139,0.00033869906],"study_design_scores_gemma":[0.006643342,0.000819598,0.0006706535,0.00054365536,0.00061680505,0.0002096452,0.00043540276,0.21682945,0.5095092,0.0017063327,0.2596853,0.0023306329],"about_ca_topic_score_codex":0.00004969328,"about_ca_topic_score_gemma":0.000021578453,"teacher_disagreement_score":0.47249675,"about_ca_system_score_codex":0.00016021589,"about_ca_system_score_gemma":0.00041781247,"threshold_uncertainty_score":0.9995486},"labels":[],"label_agreement":null},{"id":"W3028439734","doi":"10.1364/translational.2020.tw1b.6","title":"Interstitial photodynamic therapy planning with 3D placement optimization","year":2020,"lang":"en","type":"article","venue":"Biophotonics Congress: Biomedical Optics 2020 (Translational, Microscopy, OCT, OTS, BRAIN)","topic":"Photodynamic Therapy Research Studies","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":"University Health Network; University of Toronto","funders":"","keywords":"Photodynamic therapy; Diffuser (optics); Computer science; Radiation treatment planning; Medicine; Surgery; Light source; Physics; Optics; Chemistry; Radiation therapy","score_opus":0.02150779518249902,"score_gpt":0.3144293486802516,"score_spread":0.29292155349775256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3028439734","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":[0.7645663,0.00861542,0.14353704,0.0692209,0.001819997,0.0073677124,0.0021156035,0.0009825047,0.0017745362],"genre_scores_gemma":[0.8482131,0.005805498,0.11812082,0.019304134,0.001189459,0.00046434643,0.0057353517,0.00047879358,0.0006884981],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99476033,0.00015981503,0.0010614875,0.0012383538,0.0017421803,0.0010377992],"domain_scores_gemma":[0.9971772,0.0005139659,0.0003463244,0.00053324323,0.00046233565,0.0009669741],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00051064114,0.0007941224,0.0010197698,0.0003241721,0.00040913522,0.00020784797,0.00058933237,0.00043237934,0.0010890657],"category_scores_gemma":[0.00027669867,0.0006650746,0.00027083565,0.0011775948,0.0013681154,0.00026927338,0.00016536127,0.0010049281,0.00005955605],"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":[0.018297648,0.0016584535,0.0012717624,0.0008969278,0.0032692943,0.0011707349,0.004199657,0.019066883,0.9378023,0.00025357422,0.010356407,0.0017563639],"study_design_scores_gemma":[0.03523971,0.009430677,0.0012538368,0.0019528641,0.00049414864,0.00043350592,0.0014346949,0.8031647,0.05707983,0.00008554509,0.08694095,0.0024895347],"about_ca_topic_score_codex":0.00002703185,"about_ca_topic_score_gemma":0.000009664498,"teacher_disagreement_score":0.88072246,"about_ca_system_score_codex":0.00022962561,"about_ca_system_score_gemma":0.0012060235,"threshold_uncertainty_score":0.99982405},"labels":[],"label_agreement":null}]}