{"id":"W4393815867","doi":"10.5281/zenodo.2589442","title":"CIViCmine","year":2019,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Plant-based Medicinal Research","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science","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","sts","research_integrity","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002424081,0.0003816804,0.0004503043,0.0006401048,0.001893506,0.0003351133,0.002690982,0.0006514611,0.1744847],"category_scores_gemma":[0.00220664,0.0003904721,0.0001202963,0.000621472,0.0004266475,0.0001396122,0.002039574,0.003059904,0.1509791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003730936,"about_ca_system_score_gemma":0.00003280289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003735519,"about_ca_topic_score_gemma":0.00000137711,"domain_scores_codex":[0.9954784,0.001481053,0.0004529753,0.0007780747,0.0008282363,0.0009812717],"domain_scores_gemma":[0.9972262,0.0002907865,0.0002350421,0.0009386313,0.0006905564,0.000618758],"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":[0.0004043173,0.0003127099,6.062095e-7,0.0004459019,0.0001836053,0.0002130267,0.00007645137,0.00003312295,0.001531836,0.00007689242,0.9728768,0.02384468],"study_design_scores_gemma":[0.001241885,0.0005254838,0.0000233691,0.00008099382,0.0001251649,0.0002944161,0.00005755991,0.000125263,0.0003366158,0.00002363293,0.9967975,0.0003681189],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002793156,0.0003417768,0.0000486268,0.0009708712,0.0008746716,0.0009769328,0.9609172,0.0003710369,0.03521957],"genre_scores_gemma":[0.0009432069,0.0012325,0.00001702046,0.001293472,0.0006976683,1.437862e-7,0.9905646,0.00124036,0.004011073],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0312085,"threshold_uncertainty_score":0.9998547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1967440905520367,"score_gpt":0.4258320947774673,"score_spread":0.2290880042254306,"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."}}