{"id":"W2032302509","doi":"10.1155/2008/825671","title":"An Effective Multimedia Item Shell Design for Individualized Education: The Crome Project","year":2008,"lang":"en","type":"article","venue":"Advances in Multimedia","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Multimedia; Curriculum; Process (computing); Selection (genetic algorithm); Multiple choice; Computerized adaptive testing; Shell (structure); Item response theory; Representation (politics); Adaptation (eye); Human–computer interaction; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0009142727,0.0002410833,0.0002784135,0.0001877632,0.0003350635,0.00008657503,0.001018477,0.0000871579,0.000005729182],"category_scores_gemma":[0.0005848469,0.0001749958,0.00008181915,0.0004699048,0.0001274075,0.00125796,0.00007457536,0.0002646901,0.00003701716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001088263,"about_ca_system_score_gemma":0.0002404074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008899473,"about_ca_topic_score_gemma":0.0000159652,"domain_scores_codex":[0.9978774,0.0004461914,0.0003592075,0.0005699273,0.0003178992,0.0004293405],"domain_scores_gemma":[0.9966807,0.002333415,0.0002027981,0.0005209477,0.0001849524,0.00007715077],"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":[0.0001382279,0.0007002433,0.01664625,0.0001151573,0.00005639909,0.00003314381,0.05548579,0.01046996,0.001677066,0.009501919,0.0007591911,0.9044167],"study_design_scores_gemma":[0.0030487,0.001156806,0.03301175,0.0004349906,0.00002410018,0.0001130081,0.001981643,0.537424,0.01399232,0.001890547,0.4056701,0.001252066],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02059731,0.003565215,0.9674767,0.0001235553,0.00315629,0.004076022,0.000007516809,0.0002484382,0.0007490029],"genre_scores_gemma":[0.3703891,0.0002629315,0.6243066,0.0002306917,0.0008499801,0.002227243,0.00001797178,0.00004138572,0.001674135],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9031646,"threshold_uncertainty_score":0.7136121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03186338130069247,"score_gpt":0.3326963638545712,"score_spread":0.3008329825538787,"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."}}