{"id":"W4383722638","doi":"10.36227/techrxiv.16860049.v2","title":"Adaptability of Improved NEAT in Variable Environments","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Metaheuristic Optimization Algorithms Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acadia University","funders":"","keywords":"Python (programming language); Adaptability; Computer science; Data science; Programming language; Management","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":[0.002851066,0.0004648567,0.0003881088,0.0003664131,0.0006607169,0.001135214,0.001042007,0.0007599606,0.004262068],"category_scores_gemma":[0.01499519,0.0001776479,0.0004214568,0.0003759751,0.001363184,0.001621144,0.001535573,0.0008373752,0.0004947513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000650792,"about_ca_system_score_gemma":0.0005342005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006236028,"about_ca_topic_score_gemma":0.000805004,"domain_scores_codex":[0.9978805,0.001143963,0.00008796919,0.0002895901,0.0004203674,0.0001776405],"domain_scores_gemma":[0.9937372,0.00410788,0.0004031834,0.0008621498,0.000598355,0.0002913122],"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":[0.001493055,0.0009742733,0.01836849,0.002038314,0.0002582337,0.001408614,0.008411414,0.6417558,0.07967324,0.03573852,0.007735656,0.2021444],"study_design_scores_gemma":[0.0003381098,0.003076886,0.02773642,0.0004899963,0.0001718543,0.00104071,0.007383619,0.8056236,0.05391702,0.0610526,0.03882812,0.0003410956],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8222895,0.0004699803,0.1438069,0.0008061637,0.0001613823,0.0004046298,0.0004790316,0.0006609344,0.03092158],"genre_scores_gemma":[0.9676932,0.0000821612,0.03008947,0.00008959535,0.000009482084,0.0001995958,0.0001331953,0.00007684786,0.001626533],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004262068,"threshold_uncertainty_score":0.01507807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05412458107371051,"score_gpt":0.2969718087178417,"score_spread":0.2428472276441312,"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."}}