{"id":"W2020451939","doi":"10.1145/2185520.2185553","title":"Fit and diverse","year":2012,"lang":"en","type":"article","venue":"ACM Transactions on Graphics","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":165,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Ministry of Science and Technology of the People's Republic of China; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Crossover; Set (abstract data type); Population; Computer science; Diversity (politics); Fitness landscape; Artificial intelligence","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":[0.00005131958,0.00006995768,0.00006519433,0.0001156762,0.00008952228,0.00001084408,0.00005657595,0.00004858611,0.00005115768],"category_scores_gemma":[0.000003328756,0.00006874673,0.00005401131,0.0001717409,0.00001950599,0.00009390748,0.00000112491,0.0001313862,0.00002415703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006364597,"about_ca_system_score_gemma":0.000001114223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000948353,"about_ca_topic_score_gemma":0.00001324953,"domain_scores_codex":[0.9996723,0.000005856265,0.00006295076,0.00005849059,0.00006684147,0.0001335804],"domain_scores_gemma":[0.9997057,0.00003135813,0.000004524577,0.0001758503,0.000009470242,0.00007313763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003085616,0.0006177706,0.0138346,0.0002604449,0.001400265,0.000008286607,0.005387146,0.5226142,0.00168609,0.001853681,0.002390464,0.4499162],"study_design_scores_gemma":[0.002101817,0.0001980218,0.02406747,0.000158084,0.001726816,0.00005570875,0.002021623,0.9261265,0.007834642,0.007428441,0.02589989,0.002381013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4962566,0.0006072645,0.5017537,0.0001926051,0.0002748196,0.00004077603,0.00002079688,0.0003399925,0.0005134378],"genre_scores_gemma":[0.9982519,0.0006381246,0.0009328393,0.00007126187,0.00002592433,0.000004383047,0.000001346578,0.00001170121,0.00006256578],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5019952,"threshold_uncertainty_score":0.280341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03268224356594958,"score_gpt":0.2377341601293617,"score_spread":0.2050519165634122,"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."}}