{"id":"W3126336315","doi":"10.22215/etd/2019-13888","title":"Clarifying metacognition through computational modelling","year":2019,"lang":"en","type":"dissertation","venue":"","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Metacognition; Cognition; Terminology; Cognitive science; Cognitive architecture; Cognitive psychology; Abstraction; Psychology; Computer science; Epistemology; Neuroscience","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":[0.001308851,0.0007045728,0.000685317,0.0008705275,0.0005570273,0.003243211,0.002015896,0.0008987465,0.005679177],"category_scores_gemma":[0.006045662,0.0004347173,0.001329938,0.0006891684,0.002319307,0.005025783,0.00263493,0.002413359,0.0008082453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001226239,"about_ca_system_score_gemma":0.001483348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002662393,"about_ca_topic_score_gemma":0.002868194,"domain_scores_codex":[0.9992219,0.0003636069,0.00003725503,0.0001431032,0.0001682992,0.00006582231],"domain_scores_gemma":[0.9961897,0.002678122,0.0002476071,0.0006261405,0.00016369,0.00009489113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003483182,0.00005458238,0.0008044907,0.0001610418,0.00004826511,0.00005197817,0.0005112292,0.08595163,0.001007854,0.8912476,0.0005689573,0.01955751],"study_design_scores_gemma":[0.0000211963,0.00002612232,0.0003379036,0.00006844626,0.0000242763,0.00004032307,0.00009049851,0.3634005,0.0007840954,0.6272687,0.007915531,0.00002243675],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04194423,0.0005549474,0.9280534,0.001997474,0.0001063146,0.00005229373,0.0001182329,0.0001793403,0.02699371],"genre_scores_gemma":[0.6095673,0.001356097,0.3789473,0.0002904291,0.0001259198,0.0003479007,0.0002678956,0.0001639201,0.008933283],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005679177,"threshold_uncertainty_score":0.0189988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0522119205871706,"score_gpt":0.2868356614327897,"score_spread":0.2346237408456191,"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."}}