{"id":"W1611901023","doi":"10.1609/aaai.v25i1.7823","title":"The Compressed Differential Heuristic","year":2011,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Israel Science Foundation","keywords":"Uncompressed video; Heuristic; Computer science; Differential (mechanical device); Compression (physics); State (computer science); Algorithm; Computer engineering; Parallel computing; Computer hardware; Artificial intelligence; Materials science; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006007752,0.0002188944,0.0002326476,0.0001045931,0.0005220468,0.0004333159,0.004429891,0.00007130446,0.0002389472],"category_scores_gemma":[0.0008074947,0.0001289517,0.0001209534,0.000703068,0.000584877,0.0002630044,0.0007346034,0.0003763037,0.000166855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000291936,"about_ca_system_score_gemma":0.0001077563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000471596,"about_ca_topic_score_gemma":0.00000533902,"domain_scores_codex":[0.997568,0.00005357266,0.0006114616,0.0004653367,0.0008480976,0.000453547],"domain_scores_gemma":[0.9976333,0.000259395,0.0003670895,0.0005710892,0.001038328,0.0001307383],"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":[0.0000538198,0.0001474948,0.00004753638,0.0000156295,0.00001956974,5.017623e-7,0.0009261434,0.00001733445,0.003592899,0.947091,0.0003354333,0.04775266],"study_design_scores_gemma":[0.00004889808,0.0002093437,0.0007205041,0.00008558903,0.00001572471,0.00000548095,0.0003034439,0.5203477,0.2623579,0.2152912,0.0003451706,0.0002690862],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02194502,0.00007599567,0.9063594,0.005206162,0.002051735,0.001415877,0.000009087326,0.0002926318,0.06264405],"genre_scores_gemma":[0.9904695,0.00008293249,0.008533356,0.00009027202,0.00005845574,0.00004014983,2.747543e-7,0.00001372159,0.0007113221],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9685245,"threshold_uncertainty_score":0.8231913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.134526097418381,"score_gpt":0.3040097206926812,"score_spread":0.1694836232743002,"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."}}