{"id":"W3006268927","doi":"10.15252/msb.20199243","title":"Systematic genetics and single‐cell imaging reveal widespread morphological pleiotropy and cell‐to‐cell variability","year":2020,"lang":"en","type":"article","venue":"Molecular Systems Biology","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"FP7 Ideas: European Research Council; National Human Genome Research Institute; Canadian Institutes of Health Research; European Commission; National Cancer Institute; National Institutes of Health; Ministerio de Economía y Competitividad; Government of Canada; Ontario Institute for Cancer Research; Canada Research Chairs; Canadian Institute for Advanced Research","keywords":"Biology; Phenotype; Pleiotropy; Genetics; Endocytic cycle; Penetrance; Single-cell analysis; Cell; Organelle; Mutant; Gene; Endosome; Cell biology; Endocytosis","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005350556,0.0004207388,0.0005102688,0.0006199249,0.0002071484,0.000498021,0.0003245661,0.0003435093,0.0006372945],"category_scores_gemma":[0.0004821991,0.0003331139,0.0003606225,0.0003616802,0.0005649923,0.0002440601,0.0007076761,0.0007017673,0.0002366878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002977807,"about_ca_system_score_gemma":0.0002413752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005969799,"about_ca_topic_score_gemma":0.001839012,"domain_scores_codex":[0.999431,0.00006789473,0.00005500191,0.0001741538,0.0002244633,0.00004741918],"domain_scores_gemma":[0.9990717,0.0003092275,0.000273775,0.0002048375,0.00007833311,0.00006195672],"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":[0.00001257387,0.000004842881,0.0007279034,0.00001414279,0.000007138635,0.00003120919,0.00001136881,0.0001597578,0.9979385,0.00006604504,0.00001077278,0.001015763],"study_design_scores_gemma":[0.000008134185,0.00009766036,0.0481144,0.00001069557,0.00003145744,0.000777778,0.00005808444,0.007420297,0.9420918,0.0003929311,0.0009768752,0.00001999194],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9434966,0.0005228459,0.05377128,0.0000657206,0.000009917388,0.00004720081,0.0008285988,0.0004227555,0.0008351633],"genre_scores_gemma":[0.975658,0.0003454669,0.02242746,0.00006328644,0.000003475053,0.0000838171,0.0005995044,0.0001876586,0.0006312822],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006372945,"threshold_uncertainty_score":0.002829671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007575116210705145,"score_gpt":0.2298273539916899,"score_spread":0.2222522377809847,"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."}}