{"id":"W4200119498","doi":"10.1302/3114-210143","title":"CORS Paper Session: Top Canadian Research - Founder's Award Candidates Introduction","year":2021,"lang":"en","type":"dataset","venue":"OrthoMedia","topic":"scientometrics and bibliometrics research","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Library science; Computer science; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.005430115,0.002357573,0.002893979,0.01536564,0.004171486,0.009399923,0.003191322,0.001851192,0.2124819],"category_scores_gemma":[0.02210216,0.0009260323,0.002028996,0.01727315,0.001029673,0.002067245,0.004112619,0.002720439,0.1623198],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01014812,"about_ca_system_score_gemma":0.03594298,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4411588,"about_ca_topic_score_gemma":0.660306,"domain_scores_codex":[0.9947391,0.000396367,0.0003247966,0.0008189002,0.002536752,0.001184103],"domain_scores_gemma":[0.9775064,0.002742118,0.001064397,0.003123094,0.01050904,0.00505492],"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":[0.00001974749,0.000004820878,0.0002270125,0.00008709396,0.000003600956,0.000003561798,0.000007026655,0.00003646606,0.00001915707,0.0001888908,0.9979966,0.001406058],"study_design_scores_gemma":[0.0001064184,0.000008933168,0.004941786,0.0001479546,0.00001418727,0.00001047044,0.00009530839,0.0002104137,0.0001661368,0.0007124038,0.9935613,0.00002467249],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002652574,0.0001527585,0.0001510096,0.0006477459,0.000515012,0.0001436855,0.9901113,0.0009190044,0.007094225],"genre_scores_gemma":[0.001727547,0.0002053132,0.000966548,0.0003903387,0.0002202244,0.0004181698,0.9690814,0.0004553084,0.02653516],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9898519,"threshold_uncertainty_score":0.8771819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.467735534153533,"score_gpt":0.5678674728009943,"score_spread":0.1001319386474612,"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."}}