{"id":"W1572571127","doi":"10.1007/978-3-540-30139-4_68","title":"Discovering Intelligent Agent: A Tool for Helping Students Searching a Library","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Recommender Systems and Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Computer science; Task (project management); Subject (documents); Ranking (information retrieval); World Wide Web; The Internet; Pyramid (geometry); Intelligent agent; Information retrieval; Artificial intelligence; Management","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":[0.0008494096,0.0008318619,0.0007440094,0.001697833,0.0009447298,0.001864038,0.001901778,0.001730789,0.008991117],"category_scores_gemma":[0.002761119,0.0006408268,0.0005403707,0.001578094,0.0003779294,0.002552462,0.001004323,0.001334835,0.00661481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003298793,"about_ca_system_score_gemma":0.0006756886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002018845,"about_ca_topic_score_gemma":0.005491957,"domain_scores_codex":[0.9995663,0.0001128578,0.00003122518,0.00009841368,0.0001724406,0.00001884074],"domain_scores_gemma":[0.9991749,0.0004097911,0.00005556622,0.0001588292,0.0001247346,0.00007612899],"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":[0.0002890605,0.00043586,0.004265143,0.0006614348,0.000189138,0.0002883405,0.001094987,0.007361204,0.01236615,0.02778295,0.09198339,0.8532822],"study_design_scores_gemma":[0.0001689514,0.0005016874,0.005160077,0.0003087242,0.0006686799,0.002442037,0.0007254559,0.3733364,0.0505913,0.05032209,0.515542,0.0002326178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02464715,0.002562439,0.9175294,0.001573604,0.0002509511,0.000225521,0.001012845,0.02366621,0.0285319],"genre_scores_gemma":[0.05475549,0.001393311,0.9109079,0.0002024237,0.0000704914,0.0001234046,0.001233314,0.0005298297,0.03078379],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008991117,"threshold_uncertainty_score":0.03007829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02948290550404312,"score_gpt":0.2899087250841066,"score_spread":0.2604258195800635,"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."}}