{"id":"W2303754236","doi":"","title":"Towards automated content analysis of discussion transcripts: A cognitive presence case","year":2016,"lang":"en","type":"article","venue":"QUT ePrints (Queensland University of Technology)","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Overfitting; Random forest; Artificial intelligence; Cognition; Computer science; Coding (social sciences); Machine learning; Natural language processing; Context (archaeology); Set (abstract data type); Psychology; Mathematics; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.0240719,0.0008778056,0.0005750451,0.005899173,0.002406014,0.003637708,0.002488476,0.002606606,0.001411666],"category_scores_gemma":[0.1009139,0.0005490371,0.0006985302,0.002963512,0.002319786,0.004048758,0.003263681,0.001932888,0.00132436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002016611,"about_ca_system_score_gemma":0.002339176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003051858,"about_ca_topic_score_gemma":0.003894406,"domain_scores_codex":[0.9578865,0.02855611,0.001949385,0.003788762,0.006661823,0.001157341],"domain_scores_gemma":[0.8240361,0.1286254,0.009772947,0.01457002,0.02120924,0.001786269],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009484598,0.001278254,0.05614946,0.002010159,0.0001090342,0.003625718,0.1407036,0.006680068,0.1273527,0.009776382,0.005545832,0.6458203],"study_design_scores_gemma":[0.0002435674,0.001254092,0.09907466,0.001604679,0.0002516977,0.009268288,0.09757946,0.3812482,0.2738612,0.0376823,0.09737284,0.0005591186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3745117,0.0002256446,0.615064,0.001552969,0.00009103137,0.001601635,0.0007332871,0.0027693,0.003450454],"genre_scores_gemma":[0.5030319,0.0001211098,0.492927,0.0001870545,0.00007002172,0.0008802086,0.0007803997,0.0002942999,0.001708016],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0240719,"threshold_uncertainty_score":0.1273059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02202257027808128,"score_gpt":0.2504619449964253,"score_spread":0.2284393747183441,"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."}}