{"id":"W3124122716","doi":"10.1049/ell2.12083","title":"Stable ant‐antlion optimiser for feature selection on high‐dimensional data","year":2021,"lang":"en","type":"article","venue":"Electronics Letters","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Feature selection; Selection (genetic algorithm); Computer science; Feature (linguistics); ANT; Ecology; Artificial intelligence; Biology; Computer network","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001983608,0.0001425305,0.0001346238,0.00007429754,0.0002272218,0.000154761,0.0004784382,0.00008449926,0.00002941396],"category_scores_gemma":[0.00004110068,0.0001356248,0.00004776005,0.0003211263,0.00001049196,0.000568759,0.0001670493,0.000262803,0.00004053973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001019708,"about_ca_system_score_gemma":0.0001922287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006960731,"about_ca_topic_score_gemma":0.00001502364,"domain_scores_codex":[0.9984815,0.00005918647,0.0001243438,0.0006210124,0.0002781758,0.0004358392],"domain_scores_gemma":[0.9990876,0.00009456062,0.0000648342,0.0005919143,0.0001000982,0.00006097342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006243783,0.0001196542,0.00001706725,0.00001636223,0.00004727073,0.00001436194,0.00003105793,0.004785598,0.442702,0.0047798,0.5373852,0.01003925],"study_design_scores_gemma":[0.001403021,0.0002936318,0.0001905165,0.00007678225,0.00003162164,0.00006154187,0.00000620535,0.2205039,0.6360483,0.00206339,0.1388057,0.0005154894],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1883087,0.0008617424,0.7198647,0.08805972,0.001557123,0.0005784962,0.0001330045,0.0004151803,0.000221405],"genre_scores_gemma":[0.3942791,0.0004426514,0.5114838,0.08134013,0.001515185,0.0001730548,0.006772421,0.0001430581,0.003850552],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3985795,"threshold_uncertainty_score":0.5530617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01937424667944825,"score_gpt":0.2503677449615346,"score_spread":0.2309934982820863,"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."}}