{"id":"W2200387973","doi":"10.1007/978-3-642-30950-2_1","title":"Implicit Strategies for Intelligent Tutoring Systems","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Subliminal stimuli; Cognition; Intelligent tutoring system; Priming (agriculture); Human–computer interaction; Psychological intervention; Cognitive psychology; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001582577,0.0006586363,0.0007127056,0.0007382295,0.0004025678,0.001615803,0.002892811,0.0003528742,0.000007507977],"category_scores_gemma":[0.00006128685,0.0005928788,0.0002246207,0.0003284645,0.0002259289,0.001076705,0.0008798625,0.0007611107,0.00006572357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005857183,"about_ca_system_score_gemma":0.0005734719,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000078761,"about_ca_topic_score_gemma":0.00001437632,"domain_scores_codex":[0.9957502,0.00003789296,0.0007744243,0.001420764,0.0008806771,0.00113607],"domain_scores_gemma":[0.9970689,0.0005966811,0.0004557152,0.001228092,0.0004247458,0.0002258179],"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":[0.000003346502,0.00001438263,0.00003252093,0.000146903,0.00002092523,0.00001389178,0.001335289,0.08860579,0.0002256104,0.6930006,0.00001022552,0.2165905],"study_design_scores_gemma":[0.0003924454,0.0006241999,0.00006449135,0.003159481,0.00003708878,0.0002563047,0.00001290916,0.5475591,0.002645507,0.138887,0.3035342,0.002827253],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00003373486,0.003320717,0.9848145,0.00008175347,0.007611824,0.0008482254,0.000005088293,0.0002464424,0.003037707],"genre_scores_gemma":[0.5995875,0.0001981191,0.3769692,0.0005534007,0.009462617,0.0002082343,0.00001379793,0.0002345901,0.01277257],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6078454,"threshold_uncertainty_score":0.9996523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03615354413109114,"score_gpt":0.2715253767133938,"score_spread":0.2353718325823026,"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."}}