{"id":"W6892329458","doi":"10.5064/f6z31wj1/llipcd","title":"Johnson_Senate41_LCJC_15ev_20140911.pdf","year":2018,"lang":"pl","type":"dataset","venue":"Syracuse University Qualitative Data Repository","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","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","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","open_science","research_integrity","insufficient_payload"],"category_scores_codex":[0.007921407,0.003306363,0.003471242,0.002967261,0.003561721,0.0009037861,0.01811988,0.002779785,0.006358034],"category_scores_gemma":[0.00259392,0.003956346,0.0008606356,0.003067003,0.007300867,0.005973483,0.01433074,0.004053582,0.2536769],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004016377,"about_ca_system_score_gemma":0.00351867,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01234203,"about_ca_topic_score_gemma":0.002358609,"domain_scores_codex":[0.9646516,0.01886697,0.002438362,0.007356236,0.003854269,0.002832606],"domain_scores_gemma":[0.9681525,0.004489785,0.005117789,0.01716785,0.003075563,0.001996461],"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":[0.002525437,0.001365,0.00001756346,0.0009176934,0.004245289,0.005522883,0.0185201,0.000002396351,0.001043639,0.0003094098,0.9654958,0.00003479223],"study_design_scores_gemma":[0.003412053,0.0008478318,0.00005374715,0.001241935,0.00399485,0.0003171127,0.0657599,0.0001740551,0.0004521222,0.00004405062,0.9196807,0.004021694],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001699046,0.0005719173,0.0001762741,0.0001967831,0.005009208,0.001974025,0.9817874,0.0005703815,0.008014965],"genre_scores_gemma":[0.0002561352,0.0009304206,0.002004646,0.0002168221,0.002331027,0.000003892799,0.9382563,0.0004313856,0.05556937],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2473188,"threshold_uncertainty_score":0.999807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08611449078899129,"score_gpt":0.358907469187329,"score_spread":0.2727929783983377,"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."}}