{"id":"W6957885607","doi":"10.6084/m9.figshare.19625408","title":"Additional file 1 of One Cell At a Time (OCAT): a unified framework to integrate and analyze single-cell RNA-seq data","year":2022,"lang":"en","type":"article","venue":"Figshare","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute; University of Toronto; University Health Network","funders":"","keywords":"Matching (statistics); Embedding; Key (lock); Similarity (geometry); Similitude; Table (database)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001768274,0.001717349,0.001635912,0.002118174,0.001385667,0.002415265,0.003212608,0.001431011,0.7593328],"category_scores_gemma":[0.01137923,0.001118032,0.001177398,0.003056677,0.0004891584,0.002234206,0.002150712,0.001947509,0.2483218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001073174,"about_ca_system_score_gemma":0.002335883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005999255,"about_ca_topic_score_gemma":0.01197996,"domain_scores_codex":[0.9993476,0.00006389202,0.00007835474,0.0002118197,0.0001890271,0.0001092091],"domain_scores_gemma":[0.9942867,0.003399905,0.0003112562,0.0008635476,0.0007034102,0.0004351648],"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":[0.0001814155,0.00004777231,0.001066444,0.001592537,0.00005106973,0.00008878013,0.00005787422,0.001062267,0.001390093,0.001559961,0.984014,0.008887976],"study_design_scores_gemma":[0.00167859,0.0001878725,0.009858516,0.0008986495,0.0001644669,0.0006123303,0.0001756266,0.00848684,0.007953245,0.01797158,0.9517306,0.0002816463],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.0002035489,0.00003524224,0.003721064,0.00007276493,0.0000950066,0.00008076797,0.9874011,0.007047678,0.001342845],"genre_scores_gemma":[0.00719258,0.0001603466,0.02349964,0.0007704709,0.000145107,0.001336707,0.9438257,0.0153807,0.007688744],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.7593328,"threshold_uncertainty_score":0.3432826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04835531841673844,"score_gpt":0.2420072438326126,"score_spread":0.1936519254158742,"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."}}