{"id":"W2560741024","doi":"10.1083/jcb.201610026","title":"Machine learning and computer vision approaches for phenotypic profiling","year":2016,"lang":"en","type":"review","venue":"The Journal of Cell Biology","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":168,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Profiling (computer programming); Computer science; Artificial intelligence; Segmentation; Machine learning; Cluster analysis; Feature extraction; Pattern recognition (psychology)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00104849,0.0002306012,0.0007552567,0.00009671695,0.00007461298,0.00001442342,0.0003153623,0.0002903981,0.000005889868],"category_scores_gemma":[0.0000562129,0.0001116861,0.0003463837,0.00004370375,0.0001256299,0.000002810688,0.0001921551,0.0002677278,0.000002034591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001358938,"about_ca_system_score_gemma":0.00006690111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.509399e-7,"about_ca_topic_score_gemma":6.55305e-7,"domain_scores_codex":[0.9986467,0.0004365809,0.0005026323,0.0001922097,0.00004735893,0.000174483],"domain_scores_gemma":[0.9986607,0.0001731744,0.0008361276,0.0001907473,0.00009741772,0.00004178208],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005977172,0.00002358141,0.0000038747,0.0008713381,0.0002084283,8.711782e-7,0.000006726842,0.000001048418,0.02267689,0.00002441967,0.0001891564,0.9759339],"study_design_scores_gemma":[0.0001961254,0.0008170085,1.400253e-7,0.0004268808,0.0005051852,0.0001118236,0.000003461981,0.00008007765,0.009915681,0.0001118361,0.9876808,0.0001509954],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001348108,0.9633474,0.03596523,0.00001420217,0.00004100727,0.0002647757,0.000005204293,0.000004516622,0.0002228629],"genre_scores_gemma":[0.0005569938,0.9942842,0.004131522,0.00002339999,0.0005814022,0.000006882946,0.00007466791,0.00003169629,0.0003092387],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9874916,"threshold_uncertainty_score":0.4554427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02551594630556943,"score_gpt":0.3139999266580728,"score_spread":0.2884839803525034,"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."}}