{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005506958,0.0002522289,0.0003299787,0.0007635178,0.0002301212,0.0001288085,0.0006716781,0.0002184716,0.00003555694],"category_scores_gemma":[0.0005845024,0.0002553415,0.00003239685,0.001405766,0.0002316457,0.0002469924,0.0001830343,0.0011083,0.00002360712],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001084509,"about_ca_system_score_gemma":0.0006198765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007854599,"about_ca_topic_score_gemma":0.0005728201,"domain_scores_codex":[0.9979264,0.0001066602,0.0004612418,0.0006856991,0.000302446,0.0005175725],"domain_scores_gemma":[0.9985682,0.000556081,0.0001746234,0.0003842281,0.0001558197,0.0001610448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000004088087,0.0001044617,0.00901043,0.0000105598,0.000006841788,0.000006622533,0.0006543453,0.0007914759,0.0002763942,0.9633024,0.00002484464,0.0258075],"study_design_scores_gemma":[0.0004783965,0.00007733826,0.004572128,0.000216928,0.00000373451,0.00001743531,0.0001122801,0.02026248,0.0004562459,0.9734212,0.00004205837,0.0003397955],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02193528,0.001012121,0.5518242,0.4170119,0.002168452,0.0007112831,0.000002637717,0.0006963654,0.004637771],"genre_scores_gemma":[0.9837856,0.0001333721,0.01497477,0.0003581354,0.0002240728,0.000376683,0.00001463364,0.00001232363,0.0001203831],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9618503,"threshold_uncertainty_score":0.9999899,"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."}}