{"id":"W3087124925","doi":"10.1534/g3.120.401570","title":"TheCellVision.org: A Database for Visualizing and Mining High-Content Cell Imaging Projects","year":2020,"lang":"en","type":"article","venue":"G3 Genes Genomes Genetics","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Human Genome Research Institute; Canadian Institutes of Health Research","keywords":"High-content screening; Computer science; Visualization; Budding yeast; Feature (linguistics); Genome; Information retrieval; Saccharomyces cerevisiae; 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":[0.002134824,0.003058151,0.002399618,0.01393946,0.001155196,0.004902369,0.004537523,0.001858395,0.02732693],"category_scores_gemma":[0.008556284,0.001425832,0.001469495,0.01698353,0.0004933644,0.003063032,0.004710902,0.002206049,0.03596184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001450935,"about_ca_system_score_gemma":0.003006496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004807765,"about_ca_topic_score_gemma":0.006690885,"domain_scores_codex":[0.9985024,0.0001837644,0.0003144503,0.0003484942,0.0004994932,0.0001515023],"domain_scores_gemma":[0.9960148,0.001064767,0.0006043413,0.001006513,0.0006357625,0.000673792],"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":[0.0006284488,0.0001485861,0.004398153,0.005530832,0.0003412092,0.0005134188,0.0004902541,0.002236975,0.01239852,0.01107514,0.8951115,0.06712694],"study_design_scores_gemma":[0.0003971836,0.0000694983,0.00700301,0.0005797386,0.0001795392,0.000509671,0.0002811422,0.007585706,0.0109619,0.01106426,0.9611672,0.0002010243],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.002556872,0.001402635,0.02702622,0.0002600965,0.00009764695,0.0002889624,0.885579,0.07713039,0.005658102],"genre_scores_gemma":[0.005699358,0.001079324,0.04223068,0.0001372196,0.00002901377,0.0007308726,0.9421034,0.006955673,0.001034501],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.02732693,"threshold_uncertainty_score":0.09141773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04123005328445145,"score_gpt":0.2904769287856115,"score_spread":0.24924687550116,"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."}}