{"id":"W6945377241","doi":"10.25345/c5j960m3c","title":"MassIVE MSV000092781 - Tang_PAN2_3_BirA*_MassIVE_P130","year":2023,"lang":"en","type":"dataset","venue":"UC San Diego","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Sinai Health System","funders":"","keywords":"Identification (biology); Process (computing); Work (physics); Set (abstract data type)","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":[0.0009154449,0.003687814,0.002029876,0.003865091,0.001352207,0.002778745,0.003780257,0.003051516,0.113492],"category_scores_gemma":[0.003602382,0.0009649507,0.001769825,0.004315923,0.0006002926,0.001236605,0.002232931,0.001666249,0.1222487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001358381,"about_ca_system_score_gemma":0.002538101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01877173,"about_ca_topic_score_gemma":0.04013778,"domain_scores_codex":[0.9991973,0.00008618843,0.00005074513,0.0002884079,0.0002096818,0.0001677411],"domain_scores_gemma":[0.9989856,0.0002847492,0.00009294533,0.0002342978,0.000200662,0.0002018029],"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":[0.0001358732,0.00002357641,0.0007332515,0.0007525464,0.00006782296,0.00003402981,0.00002327451,0.0003569066,0.0005446774,0.0005844631,0.9941485,0.00259508],"study_design_scores_gemma":[0.0006898841,0.00005186209,0.004191943,0.0002812607,0.0001463828,0.0001496844,0.0000677475,0.001662049,0.00188683,0.003917044,0.986886,0.00006918399],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003318517,0.0001543033,0.0001461307,0.00007612439,0.00003020869,0.00001393433,0.9958669,0.002039263,0.001341283],"genre_scores_gemma":[0.0009104774,0.00007980462,0.0005444471,0.00008693074,0.000008698983,0.00006658521,0.9970492,0.000312609,0.0009413346],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.886508,"threshold_uncertainty_score":0.3796686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009830065763616747,"score_gpt":0.2794014969469528,"score_spread":0.2695714311833361,"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."}}