{"id":"W2015663441","doi":"10.4018/jcini.2007070102","title":"AURELLIO","year":2007,"lang":"en","type":"article","venue":"International Journal of Cognitive Informatics and Natural Intelligence","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Representation (politics); Cognition; Knowledge representation and reasoning; Field (mathematics); Artificial intelligence; Cognitive model; Cognitive science; Computational model; Mechanism (biology); Human intelligence; 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":[],"consensus_categories":[],"category_scores_codex":[0.001081334,0.0001218773,0.0001573583,0.0003609099,0.00006186251,0.0002395884,0.0006982047,0.00004865291,0.00001004148],"category_scores_gemma":[0.0003844266,0.0000940447,0.0000923533,0.0001592609,0.00005495149,0.001124801,0.0001527709,0.0003868928,0.00002385177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004698171,"about_ca_system_score_gemma":0.00004619346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006487779,"about_ca_topic_score_gemma":0.000001753919,"domain_scores_codex":[0.9983245,0.00001986291,0.0008039732,0.0000721004,0.0005936004,0.0001859227],"domain_scores_gemma":[0.9970167,0.0005404617,0.0006072652,0.0000648954,0.001672639,0.00009798753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001091495,0.00005181973,0.001316453,0.00001533201,0.0002208517,0.0001832313,0.006655212,0.0001465997,0.0002818573,0.3092264,0.00006817251,0.6817249],"study_design_scores_gemma":[0.003981549,0.003423237,0.04029045,0.00975044,0.0001974607,0.01970868,0.04633517,0.1591664,0.3661895,0.05346727,0.2936036,0.003886252],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05443375,0.0006357793,0.9403511,0.0001220736,0.002233299,0.00005368983,0.00000111099,0.00001590299,0.002153251],"genre_scores_gemma":[0.9826903,0.0002138173,0.01600495,0.0003817429,0.0002837376,3.286118e-7,8.830255e-7,0.000004146705,0.0004201191],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9282565,"threshold_uncertainty_score":0.3835031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01468219410358645,"score_gpt":0.2950738930123826,"score_spread":0.2803916989087961,"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."}}