{"id":"W1649668773","doi":"","title":"Applying Bayesian Belief Networks in Learning Object Quality Rating","year":2004,"lang":"en","type":"article","venue":"EdMedia: World Conference on Educational Media and Technology","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Object (grammar); Artificial intelligence; Bayesian network; Computer science; Quality (philosophy); Machine learning; Bayesian probability; Psychology; Epistemology","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":[0.01153696,0.0009681369,0.001454636,0.004362908,0.0006249996,0.002883089,0.002121658,0.002466324,0.002480153],"category_scores_gemma":[0.0635635,0.001046631,0.001029941,0.002654142,0.0008981224,0.004490529,0.001670506,0.002394779,0.0006704741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002031274,"about_ca_system_score_gemma":0.0009810415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01773641,"about_ca_topic_score_gemma":0.01507646,"domain_scores_codex":[0.9933128,0.003563561,0.000463852,0.0008451995,0.001614522,0.0002000455],"domain_scores_gemma":[0.9584196,0.03535439,0.001403922,0.00133533,0.003129942,0.0003567949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008871225,0.0005733948,0.01855481,0.0002586468,0.0004938534,0.0001044159,0.0003097397,0.5272857,0.001474584,0.02190753,0.002950125,0.4252],"study_design_scores_gemma":[0.00001912815,0.00001727747,0.0008825636,0.00001223202,0.00002575695,0.00001031198,0.00001313581,0.9871957,0.0003661257,0.01126265,0.0001824486,0.00001261984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04762088,0.0006794169,0.9483743,0.0004924374,0.00006065792,0.0001397105,0.0001968265,0.0005863861,0.001849338],"genre_scores_gemma":[0.7742795,0.000422592,0.2228533,0.0001259378,0.0001118029,0.0001669433,0.000438419,0.00008944546,0.001512023],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01773641,"threshold_uncertainty_score":0.061014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03437754829005806,"score_gpt":0.2923583837856111,"score_spread":0.2579808354955531,"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."}}