{"id":"W4406089582","doi":"","title":"Keynote: What We Talk About When We Talk About Evidence","year":2013,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Evaluation and Performance Assessment","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Data science; History","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02268786,0.001798866,0.002475418,0.003425024,0.007412252,0.01640506,0.002824449,0.04012883,0.08014596],"category_scores_gemma":[0.1820729,0.001406646,0.001969246,0.003030178,0.007107235,0.02463621,0.008175029,0.05926612,0.04407832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006448084,"about_ca_system_score_gemma":0.008280325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003909242,"about_ca_topic_score_gemma":0.004988628,"domain_scores_codex":[0.976441,0.009434585,0.00469829,0.002125004,0.005374629,0.001926549],"domain_scores_gemma":[0.8542799,0.09361964,0.007994081,0.003231623,0.02614428,0.01473052],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000351164,0.000007537892,0.00006091853,0.0001790403,0.000009022699,0.00006575415,0.0001927534,0.00001197676,0.00008485735,0.003975973,0.9909314,0.004445565],"study_design_scores_gemma":[0.00003794066,0.0000262973,0.0003331974,0.001042328,0.00002381761,0.000218299,0.00109304,0.0000432636,0.00008717139,0.01059093,0.9864559,0.0000479495],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00006135747,0.003559475,0.000472429,0.7686051,0.2229464,0.00003557379,0.0001853217,0.00005055148,0.004083721],"genre_scores_gemma":[0.001810883,0.003022857,0.0008153465,0.7620864,0.2100788,0.0001662891,0.000139677,0.0002192692,0.02166053],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9773121,"threshold_uncertainty_score":0.2681149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5974596579464728,"score_gpt":0.6540836632870419,"score_spread":0.05662400534056911,"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."}}