{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002193533,0.0005512479,0.0005321009,0.0002627928,0.0001120135,0.00009160128,0.0009135018,0.0007641031,0.0005336609],"category_scores_gemma":[0.000401353,0.0005441747,0.0004556155,0.0003008899,0.0001787526,0.00000383002,0.0007433373,0.0004055725,0.002854064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005310597,"about_ca_system_score_gemma":0.0001277211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003168833,"about_ca_topic_score_gemma":0.001367487,"domain_scores_codex":[0.9975317,0.0001213759,0.0004344792,0.00101194,0.0003550388,0.0005454401],"domain_scores_gemma":[0.9975282,0.00003758364,0.0003223521,0.001773113,0.0001747146,0.0001640364],"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":[0.00002056886,0.00006250067,0.00002255137,0.00006681932,0.0002952788,0.000147218,0.000002531392,0.000002097917,0.01731204,0.000002512632,0.9816136,0.0004522555],"study_design_scores_gemma":[0.000184153,0.0001651086,0.00005972186,0.00004968779,0.0002404188,0.000008556392,0.00002068695,0.000003577928,0.03303126,0.00007371428,0.9655654,0.0005977113],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002174775,0.0009824804,0.0001290929,0.00009346741,0.000241388,0.0003968049,0.9960533,0.0001563767,0.001729546],"genre_scores_gemma":[0.0001525126,0.001492058,0.0001944219,0.0006806965,0.0009144518,0.000134133,0.9879371,0.0001022847,0.008392341],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01604822,"threshold_uncertainty_score":0.999701,"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."}}