{"id":"W4321612302","doi":"10.32920/22149035.v1","title":"TheCellVision.org: A Database for Visualizing and Mining High-Content Cell Imaging Projects","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research; National Institutes of Health","keywords":"High-content screening; Visualization; Computer science; Budding yeast; Information retrieval; Saccharomyces cerevisiae; Genome; Computational biology; Data mining; Biology; Cell; Yeast","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":[0.00208023,0.00369095,0.002733013,0.01277368,0.001250473,0.005825878,0.005172322,0.002213963,0.03715509],"category_scores_gemma":[0.008439559,0.001724395,0.001684009,0.0161366,0.0005581026,0.003634541,0.005026635,0.00274368,0.06263094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001433809,"about_ca_system_score_gemma":0.003161616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004565461,"about_ca_topic_score_gemma":0.00578359,"domain_scores_codex":[0.9983214,0.000208963,0.0003048838,0.0003887478,0.0005970644,0.0001789716],"domain_scores_gemma":[0.996392,0.0008565515,0.0004909532,0.001084297,0.0006026124,0.0005737055],"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":[0.0003440662,0.00008220934,0.002013897,0.003496415,0.0002342192,0.0003300957,0.0003014581,0.001479038,0.006464434,0.008648996,0.9356532,0.04095182],"study_design_scores_gemma":[0.0003123034,0.00003971545,0.004053182,0.0003954894,0.000122021,0.000421999,0.0001850252,0.005714001,0.007743993,0.01353032,0.9673197,0.0001623023],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001602779,0.001388689,0.03225433,0.0002807023,0.0001449411,0.0002159093,0.8638785,0.09317218,0.007062001],"genre_scores_gemma":[0.003965579,0.001049606,0.03557062,0.000130812,0.00003344481,0.0005163365,0.9471625,0.01033196,0.001239164],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03715509,"threshold_uncertainty_score":0.1242962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06250129483754029,"score_gpt":0.335928897146145,"score_spread":0.2734276023086047,"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."}}