{"id":"W1515502002","doi":"","title":"Building Computer-based Tutors to Help Learners Solve Ill-Structured Problems","year":2010,"lang":"en","type":"article","venue":"EdMedia: World Conference on Educational Media and Technology","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Seneca Polytechnic","funders":"","keywords":"Computer science; Mathematics education; Human–computer interaction; Multimedia; Psychology","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":[0.001342359,0.0008499908,0.0005019121,0.0005850278,0.000588013,0.00141031,0.001739665,0.001615623,0.007305596],"category_scores_gemma":[0.01037481,0.0004065502,0.0003477573,0.0002503407,0.0003306422,0.001917787,0.001922575,0.0009913137,0.002999082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004000451,"about_ca_system_score_gemma":0.000868938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005339129,"about_ca_topic_score_gemma":0.001085181,"domain_scores_codex":[0.9992048,0.0003143749,0.00004823877,0.0002259652,0.0001422975,0.00006429497],"domain_scores_gemma":[0.9966316,0.001538366,0.0002238466,0.0003938992,0.000727719,0.000484659],"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":[0.0006427438,0.01031803,0.03358257,0.0007046111,0.0001220135,0.001467726,0.009415193,0.0222136,0.06207722,0.004708434,0.02598624,0.8287616],"study_design_scores_gemma":[0.001733277,0.01134707,0.02849349,0.0005644534,0.0008860784,0.004176985,0.01259824,0.5536539,0.1862827,0.02642971,0.1734892,0.0003450006],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6165765,0.0004186135,0.3389358,0.0009303369,0.0003161093,0.00157503,0.0002795927,0.01846775,0.0225003],"genre_scores_gemma":[0.5895277,0.000317344,0.393249,0.0003679253,0.00004674278,0.0008605282,0.0006174671,0.0002547206,0.01475854],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007305596,"threshold_uncertainty_score":0.02443963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02238489015550107,"score_gpt":0.261761569467057,"score_spread":0.2393766793115559,"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."}}