{"id":"W3007006485","doi":"","title":"Proceedings of the International Conference on Educational Data Mining (EDM) (12th, Montreal, Canada, July 2-5, 2019).","year":2019,"lang":"en","type":"article","venue":"Educational Data Mining","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal; Polytechnique Montréal","funders":"","keywords":"Library science; Computer science; Data science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0004512325,0.0001646932,0.0001648439,0.0001015013,0.0001481048,0.0002224689,0.006618692,0.00004494991,0.0002805152],"category_scores_gemma":[0.0006507752,0.0001394984,0.00002485922,0.0003194799,0.00005484296,0.0009716322,0.001695285,0.0002296607,0.00005816935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001036498,"about_ca_system_score_gemma":0.004379112,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01566664,"about_ca_topic_score_gemma":0.009716787,"domain_scores_codex":[0.997804,0.00001868912,0.0003654295,0.0007283253,0.0008495839,0.0002339651],"domain_scores_gemma":[0.9973632,0.0004069658,0.0003648429,0.001402419,0.000371385,0.00009126183],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.000007807137,0.0002175899,0.05587587,0.00002848265,0.00007937121,3.330078e-7,0.0006302287,0.0001194812,0.0002919231,0.03917197,0.8987951,0.00478189],"study_design_scores_gemma":[0.000768584,0.00008633936,0.4774905,0.0008978292,0.00006538313,0.00006664546,0.001680738,0.4044855,0.000198477,0.003734077,0.1096805,0.000845391],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5746018,0.0002222816,0.000228241,0.3507437,0.008623702,0.0004254094,0.003015127,0.00006161745,0.06207808],"genre_scores_gemma":[0.9478743,0.00001858071,0.0284793,0.001130845,0.000894011,0.000006832931,0.002599388,0.00001826288,0.01897844],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7891145,"threshold_uncertainty_score":0.998756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05317215898791266,"score_gpt":0.3117296446957465,"score_spread":0.2585574857078339,"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."}}