{"id":"W2891780261","doi":"10.1186/s12909-018-1322-z","title":"Development and initial validation of an online engagement metric using virtual patients","year":2018,"lang":"en","type":"article","venue":"BMC Medical Education","topic":"Online and Blended Learning","field":"Social Sciences","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Uniformed Services University of the Health Sciences; Dartmouth College","keywords":"Metric (unit); Confirmatory factor analysis; Student engagement; Psychology; Accreditation; Applied psychology; Medical education; Mathematics education; Computer science; Structural equation modeling; Medicine; Machine learning; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.05042168,0.000636721,0.0004586914,0.002678694,0.0007506644,0.002193715,0.001792623,0.0008694863,0.001290822],"category_scores_gemma":[0.1139974,0.0003031708,0.0009366276,0.001268624,0.001339559,0.001440502,0.002927371,0.001039073,0.0005077341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001582318,"about_ca_system_score_gemma":0.003137064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001453129,"about_ca_topic_score_gemma":0.001801145,"domain_scores_codex":[0.9501026,0.03038245,0.006154017,0.001612959,0.01057958,0.001168292],"domain_scores_gemma":[0.8776384,0.05453812,0.01007096,0.00913546,0.04547298,0.003144126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001532401,0.003360446,0.6410611,0.0008048563,0.0002415744,0.0002262767,0.009069473,0.004831028,0.01006299,0.002920801,0.00235945,0.3235295],"study_design_scores_gemma":[0.0006668337,0.02059674,0.8351229,0.0009228872,0.000317156,0.001079098,0.009499367,0.06143444,0.0399721,0.003098166,0.02703674,0.0002535864],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9191716,0.0001195496,0.06665798,0.0003863996,0.00007721973,0.007757174,0.0006478499,0.0003192742,0.004863028],"genre_scores_gemma":[0.8737594,0.0001019857,0.117222,0.0001114473,0.00003324567,0.007182383,0.001021628,0.00005224027,0.0005156542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05042168,"threshold_uncertainty_score":0.2666585,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09546042852203879,"score_gpt":0.4234557687552165,"score_spread":0.3279953402331777,"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."}}