{"id":"W54112846","doi":"10.1007/978-1-4615-1681-1_3","title":"Software Techniques for Efficient Polymorphic Calls","year":2001,"lang":"en","type":"book-chapter","venue":"","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Section (typography); Software; Operating system","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":[0.0007274598,0.001004834,0.0007128922,0.001144108,0.0009348427,0.001486069,0.002206235,0.001140887,0.01135093],"category_scores_gemma":[0.003898189,0.0009734709,0.001166166,0.002075336,0.001399633,0.002955419,0.00200798,0.003307304,0.004526287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004708769,"about_ca_system_score_gemma":0.0007095315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003903686,"about_ca_topic_score_gemma":0.0007145015,"domain_scores_codex":[0.9990227,0.0001600527,0.00005191502,0.000109283,0.0005573046,0.00009868696],"domain_scores_gemma":[0.9987047,0.0006329675,0.00005949097,0.0004340289,0.0001465271,0.00002227775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006355772,0.00005719445,0.0002249549,0.0003728121,0.00003732117,0.0001160496,0.0003788837,0.01005996,0.01254956,0.3887199,0.01380203,0.5736178],"study_design_scores_gemma":[0.00008838083,0.000101194,0.0004489347,0.0002490883,0.0001247091,0.001031353,0.0001219467,0.1229958,0.02377284,0.6570244,0.1939754,0.00006592034],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003296906,0.0007992896,0.9798427,0.0001618537,0.00009386039,0.00004521886,0.00004131195,0.002007614,0.01371121],"genre_scores_gemma":[0.07669653,0.002058725,0.8917732,0.0001989068,0.0001629981,0.0002805913,0.0002633589,0.001839027,0.02672679],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01135093,"threshold_uncertainty_score":0.03797263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01946262031291814,"score_gpt":0.2457890954890806,"score_spread":0.2263264751761624,"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."}}