{"id":"W6948784027","doi":"10.5064/f6z31wj1/6b8kl6","title":"Johnson_Senate41_LCJC_15ev_20140910.pdf","year":2023,"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":[0.008567961,0.003127794,0.003537144,0.003882207,0.003113643,0.0008543159,0.01695162,0.002613314,0.001322955],"category_scores_gemma":[0.003537584,0.003843896,0.0009359567,0.004899854,0.003850246,0.005130941,0.01175018,0.004851866,0.6780213],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004097024,"about_ca_system_score_gemma":0.00329739,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03089244,"about_ca_topic_score_gemma":0.004179124,"domain_scores_codex":[0.9657372,0.01765214,0.002459794,0.007114041,0.004123952,0.002912862],"domain_scores_gemma":[0.9684682,0.007893141,0.004465127,0.01533059,0.001966555,0.001876353],"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":[0.001639227,0.001227796,0.00001430137,0.001202439,0.004692379,0.01414896,0.01156034,0.00001553304,0.001072591,0.0003870856,0.9639817,0.00005768033],"study_design_scores_gemma":[0.003126062,0.0004261307,0.0001346693,0.001294099,0.00353539,0.0001907217,0.1010351,0.0002066458,0.00017514,0.00004669494,0.8861334,0.003695982],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006911584,0.0004430264,0.00008429346,0.0003573282,0.005993552,0.002037048,0.9830482,0.001287168,0.006058217],"genre_scores_gemma":[0.00008186717,0.001449146,0.0006483609,0.0001414141,0.001200145,0.000005510877,0.8722609,0.0005885264,0.1236242],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6766984,"threshold_uncertainty_score":0.9997261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1199575240868993,"score_gpt":0.3709385309667765,"score_spread":0.2509810068798772,"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."}}