{"id":"W2982223312","doi":"10.2144/btn-2019-0067","title":"Single-cell Analysis for Drug Development Using Convex Lens-Induced Confinement Imaging","year":2019,"lang":"en","type":"article","venue":"BioTechniques","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Drug discovery; Single-cell analysis; Cell; Population; Cell growth; Live cell imaging; Cell biology; Biology; Computational biology; Biological system; Bioinformatics; Genetics; Medicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004368977,0.000273807,0.0003653953,0.0002955091,0.00009003376,0.00006856163,0.0002816689,0.0001598189,0.00005467294],"category_scores_gemma":[0.00002282114,0.0002789572,0.000315316,0.0002846869,0.00004067065,0.00001067923,0.0001739681,0.00008709182,0.000006730524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008363964,"about_ca_system_score_gemma":0.00009604136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008507787,"about_ca_topic_score_gemma":0.00003348778,"domain_scores_codex":[0.998378,0.00005029254,0.0004201434,0.0006304082,0.000176291,0.0003449102],"domain_scores_gemma":[0.9988585,0.00001575551,0.000219791,0.000630028,0.0002153694,0.00006060508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002483082,0.00009774592,0.003224674,0.00003170026,0.0002379265,0.000001182854,0.00003437971,0.000004332922,0.9926434,0.00001147383,0.001817044,0.001871301],"study_design_scores_gemma":[0.0002228269,0.00007904847,0.0001131642,0.00001574967,0.0002298287,0.000001737206,0.000049659,0.0006578086,0.9171892,0.00001112773,0.08107612,0.0003537105],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8307272,0.0003364947,0.1652496,0.00009059075,0.00003032377,0.0008790318,0.000006557435,0.0001857255,0.002494497],"genre_scores_gemma":[0.9186314,0.00004142944,0.07969949,0.0004150743,0.00006183623,0.00006674461,0.0002314338,0.00003963941,0.0008128977],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08790431,"threshold_uncertainty_score":0.9999663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01965267023926966,"score_gpt":0.2679658649665571,"score_spread":0.2483131947272874,"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."}}