{"id":"W2102473090","doi":"10.1109/aamas.2004.130","title":"From Global Selective Perception to Local Selective Perception","year":2004,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Reinforcement learning; Computer science; Perception; Task (project management); Artificial intelligence; Machine learning; Human–computer interaction; Engineering; 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":[0.0007698335,0.0005609698,0.0004161925,0.0002345367,0.0003769813,0.001236482,0.0009646891,0.0007570367,0.002426175],"category_scores_gemma":[0.002127253,0.0002975905,0.0003909177,0.0002551217,0.002355999,0.002749075,0.001738316,0.001795711,0.0003726478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006820279,"about_ca_system_score_gemma":0.0005341338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00155061,"about_ca_topic_score_gemma":0.001179351,"domain_scores_codex":[0.999537,0.0001410768,0.00001510447,0.000134166,0.0001088777,0.00006377554],"domain_scores_gemma":[0.9991336,0.0004430637,0.00007358076,0.0001491682,0.0001123062,0.00008816565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003481723,0.00009590741,0.001496207,0.0003302066,0.0001108045,0.0002333897,0.000844689,0.1947246,0.01841692,0.5123587,0.004404861,0.2666356],"study_design_scores_gemma":[0.00004750868,0.000178616,0.0006821891,0.00004120829,0.00005504086,0.0001282589,0.0001223953,0.6697857,0.006285681,0.3135176,0.009121845,0.00003389902],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01695636,0.001170767,0.9685115,0.0007633857,0.00007889011,0.00002559519,0.00002243562,0.0003566462,0.01211454],"genre_scores_gemma":[0.7960113,0.001301105,0.1955053,0.0005273386,0.0001469827,0.0000942853,0.00005907435,0.000164559,0.006190072],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002426175,"threshold_uncertainty_score":0.008116364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009403027730984318,"score_gpt":0.2610425284360794,"score_spread":0.2516395007050951,"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."}}