{"id":"W4360951525","doi":"10.1101/2023.03.23.534023","title":"JUMP Cell Painting dataset: morphological impact of 136,000 chemical and genetic perturbations","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"Amgen (Canada)","funders":"","keywords":"Upload; Profiling (computer programming); Painting; Computer science; Computational biology; Biology; Database; World Wide Web; Art; Visual arts; Operating system","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":[0.000957371,0.002328599,0.001648744,0.002405441,0.001064412,0.001899358,0.002687573,0.00302826,0.00764862],"category_scores_gemma":[0.002093996,0.0004900586,0.002386756,0.002600885,0.0006636382,0.0008166914,0.002010122,0.001887092,0.01096855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001482648,"about_ca_system_score_gemma":0.001162613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01439382,"about_ca_topic_score_gemma":0.02728615,"domain_scores_codex":[0.9986327,0.0001076912,0.00008475899,0.0003674081,0.0006185899,0.0001887626],"domain_scores_gemma":[0.9989151,0.0002471089,0.00006971435,0.0003909959,0.000267401,0.0001097432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007176166,0.0004759046,0.01037115,0.002337357,0.0004459264,0.0005182563,0.00008754307,0.01179851,0.02134187,0.001227008,0.9201363,0.03054249],"study_design_scores_gemma":[0.0007415643,0.0005077563,0.09360793,0.0004581136,0.0003980923,0.00220587,0.0004762755,0.04030413,0.05408969,0.00568438,0.8012188,0.0003073377],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02128314,0.00162284,0.001592949,0.0005249758,0.0002186925,0.00008450586,0.9669372,0.004578587,0.003156922],"genre_scores_gemma":[0.01004129,0.0002721933,0.00224401,0.000125686,0.00002019443,0.00007685631,0.9861924,0.0001651344,0.0008621083],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01439382,"threshold_uncertainty_score":0.02862006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01356820234569218,"score_gpt":0.2526914450220081,"score_spread":0.239123242676316,"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."}}