{"id":"W2092822077","doi":"10.1002/ajpa.21637","title":"Technical note: Quantitative measures of iris color using high resolution photographs","year":2011,"lang":"en","type":"article","venue":"American Journal of Physical Anthropology","topic":"melanin and skin pigmentation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Color space; IRIS (biosensor); Eye color; Hue; Sample (material); Artificial intelligence; Computer vision; Computer science; Biology; Genetics; Biometrics; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02843677,0.001079187,0.00106088,0.003024397,0.001299974,0.001691718,0.003476235,0.00167802,0.02152495],"category_scores_gemma":[0.04469383,0.001478918,0.001255407,0.001892456,0.001821248,0.001735999,0.002357925,0.002979901,0.01158433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006335005,"about_ca_system_score_gemma":0.001071809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001636153,"about_ca_topic_score_gemma":0.00395999,"domain_scores_codex":[0.9746684,0.01009945,0.002270153,0.002704946,0.009838361,0.0004188207],"domain_scores_gemma":[0.9381558,0.01660814,0.003100223,0.02016146,0.02077066,0.001203765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001881475,0.0005779364,0.03543009,0.004054488,0.000392992,0.001496029,0.001764861,0.001328186,0.4153546,0.01349379,0.1186915,0.4055341],"study_design_scores_gemma":[0.0004145795,0.002601204,0.1497867,0.0009612586,0.0006103654,0.02052238,0.001017903,0.01734358,0.3344379,0.009552003,0.4621052,0.0006469205],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02855814,0.00289829,0.925674,0.00578014,0.007739346,0.006263387,0.004017488,0.004347509,0.01472169],"genre_scores_gemma":[0.05842927,0.001635495,0.9030715,0.002150254,0.001366234,0.009502389,0.001807408,0.001158671,0.02087883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02843677,"threshold_uncertainty_score":0.1503898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03700229005011069,"score_gpt":0.3339910688603304,"score_spread":0.2969887788102197,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}