{"id":"W4387343342","doi":"10.1016/j.chembiol.2023.09.003","title":"A machine learning and live-cell imaging tool kit uncovers small molecules induced phospholipidosis","year":2023,"lang":"en","type":"article","venue":"Cell chemical biology","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Genentech; Fundación Bancaria Caixa d'Estalvis i Pensions de Barcelona; Deutsche Forschungsgemeinschaft; Deutschen Konsortium für Translationale Krebsforschung; Ontario Genomics Institute; European Federation of Pharmaceutical Industries and Associations; Merck KGaA; McGill University; Innovative Health Initiative; Ontario Genomics; Genome Canada; Fundação de Amparo à Pesquisa do Estado de São Paulo; Bayer; Pfizer","keywords":"Phospholipidosis; Drug discovery; Small molecule; High-content screening; Computer science; Chemical biology; Computational biology; Chemistry; Artificial intelligence; Cell; Machine learning; Biology; Biochemistry; Phospholipid; Membrane","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004443295,0.0005604388,0.000501251,0.0007420753,0.0002912959,0.0008725608,0.00118883,0.001049389,0.003814414],"category_scores_gemma":[0.0009345903,0.0003380129,0.0004953671,0.0003568449,0.0002728717,0.0007314591,0.0006671736,0.0009588795,0.001009883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004042275,"about_ca_system_score_gemma":0.0006521704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004120228,"about_ca_topic_score_gemma":0.0009242882,"domain_scores_codex":[0.9997988,0.00002333031,0.000009802546,0.00004605857,0.00009950189,0.0000225507],"domain_scores_gemma":[0.9995067,0.0002618698,0.00008932815,0.00004931691,0.00005353699,0.00003927113],"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":[0.0004169232,0.0003567766,0.006096643,0.0008044587,0.00020173,0.0006952999,0.00007664432,0.0338768,0.7482505,0.007033225,0.01361112,0.1885799],"study_design_scores_gemma":[0.00007104728,0.0002168791,0.002654346,0.00002568673,0.00004755033,0.0004546361,0.00002892764,0.5209659,0.460585,0.004064937,0.01083212,0.00005298717],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4124855,0.001008925,0.5311933,0.0015897,0.0002256996,0.0002374808,0.006936786,0.04011059,0.006212072],"genre_scores_gemma":[0.5552459,0.0007944155,0.4306407,0.0006255922,0.00005400099,0.0004560974,0.005368148,0.0009593837,0.005855774],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003814414,"threshold_uncertainty_score":0.01276052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01766000720713175,"score_gpt":0.2649485855534669,"score_spread":0.2472885783463351,"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."}}