{"id":"W2262145660","doi":"","title":"Using Cognitive Artifacts for Learning","year":2007,"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":"Simon Fraser University","funders":"","keywords":"Computer science; Cognition; Artificial intelligence; 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":[0.003007597,0.0009722483,0.0002304856,0.002228292,0.001366547,0.0130318,0.001371516,0.001751396,0.0084727],"category_scores_gemma":[0.009471091,0.000418413,0.0008497868,0.001376216,0.00302863,0.008239693,0.00557155,0.0016511,0.002772903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008530765,"about_ca_system_score_gemma":0.001399482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009325547,"about_ca_topic_score_gemma":0.001160736,"domain_scores_codex":[0.9961625,0.001897798,0.0002399029,0.0004087336,0.001077733,0.0002132233],"domain_scores_gemma":[0.9902942,0.003871077,0.000383515,0.004281139,0.0008096874,0.0003603002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009075662,0.0002996253,0.003382766,0.0005547717,0.00005759079,0.001005109,0.0266558,0.001431567,0.01343775,0.6122038,0.006893485,0.333987],"study_design_scores_gemma":[0.00007697912,0.000289737,0.003313668,0.0007582655,0.0001756969,0.002321441,0.009109176,0.01045637,0.04423548,0.2985725,0.6305808,0.0001098326],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06688656,0.001395842,0.6538124,0.002565998,0.0003644193,0.0002625472,0.0002282379,0.003364848,0.2711192],"genre_scores_gemma":[0.6908622,0.001149767,0.2469275,0.0005065216,0.00008084672,0.0002678255,0.0004262016,0.000577556,0.0592015],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0130318,"threshold_uncertainty_score":0.02834404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08894508763488225,"score_gpt":0.3291799762146349,"score_spread":0.2402348885797526,"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."}}