{"id":"W2912852114","doi":"10.1002/pra2.2018.14505501119","title":"Video‐based consensus annotations for learning: A feasibility study","year":2018,"lang":"en","type":"article","venue":"Proceedings of the Association for Information Science and Technology","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Software deployment; Multimedia; Online video; World Wide Web; Information retrieval; Human–computer interaction","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":[0.02402724,0.0008223479,0.0004222749,0.001668094,0.001382606,0.001594032,0.00266028,0.001694206,0.002863546],"category_scores_gemma":[0.07568677,0.0005404148,0.0005412829,0.001035019,0.001037808,0.002975577,0.002147812,0.001175118,0.0009218091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001074714,"about_ca_system_score_gemma":0.001824368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004380535,"about_ca_topic_score_gemma":0.006045779,"domain_scores_codex":[0.9837588,0.01173398,0.0006651339,0.001214214,0.001996863,0.0006309754],"domain_scores_gemma":[0.8926009,0.08002837,0.003658189,0.006947976,0.01268531,0.004079216],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01165718,0.04410436,0.1989371,0.003472753,0.0003900888,0.003719863,0.05670021,0.01211092,0.08520852,0.002935882,0.007576546,0.5731866],"study_design_scores_gemma":[0.008745468,0.1447027,0.3806547,0.001195254,0.001003315,0.003114769,0.1040112,0.1944605,0.1162588,0.007646804,0.03724204,0.0009644698],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9609687,0.00004558107,0.03033888,0.0003950556,0.00005864442,0.005352489,0.0004768919,0.0005094588,0.001854347],"genre_scores_gemma":[0.9198421,0.00004736182,0.0737204,0.0001419294,0.00004720963,0.004973873,0.0003844745,0.00007427017,0.0007684749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02402724,"threshold_uncertainty_score":0.1270697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01685244239651851,"score_gpt":0.3005253465946058,"score_spread":0.2836729041980873,"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."}}