{"id":"W2044714978","doi":"10.1086/498276","title":"Alternative Designs and the Evolution of Functional Diversity","year":2005,"lang":"en","type":"article","venue":"The American Naturalist","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":269,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Trait; Biology; Functional diversity; Fitness landscape; Diversity (politics); Evolutionary biology; Niche; Selection (genetic algorithm); Adaptation (eye); Tree (set theory); Fitness function; Experimental evolution; Ecological niche; Ecology; Computer science; Artificial intelligence; Mathematics; Machine learning; Genetic algorithm; Population","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":[0.0001921294,0.00003716497,0.00006468992,0.000007049766,0.0003798329,0.000002618056,0.000101564,0.000006536245,0.00008355399],"category_scores_gemma":[0.00003614833,0.00001905164,0.00002097987,0.00009463434,0.002244614,0.00005440293,0.0002341544,0.0000690212,0.00002901588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008639544,"about_ca_system_score_gemma":0.000002289589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002640533,"about_ca_topic_score_gemma":0.001270719,"domain_scores_codex":[0.9996452,0.00008573687,0.00005174112,0.00007079173,0.00008831581,0.00005825652],"domain_scores_gemma":[0.9996037,0.0002176203,0.00009557544,0.0000660431,0.000007852641,0.000009166041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008875904,0.00008021926,0.8357947,0.000003333019,0.0002083905,8.897798e-7,0.008484352,0.02673511,0.0009032322,0.1120676,0.005918847,0.008915762],"study_design_scores_gemma":[0.0002665672,0.00001717826,0.9838395,6.870114e-7,0.00002033579,0.000002976682,0.000545965,0.009528296,0.00001920204,0.005583624,0.0001405478,0.00003518935],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908323,0.00009045937,0.001277675,0.004427288,0.0000383315,0.00007167525,0.000003130335,0.000005919274,0.003253184],"genre_scores_gemma":[0.9988148,0.0000351036,0.0001398437,0.0005188319,0.00001966618,0.000002564242,6.46071e-7,0.000001085455,0.0004674924],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1480448,"threshold_uncertainty_score":0.8270373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01211372304749569,"score_gpt":0.2258214908714281,"score_spread":0.2137077678239324,"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."}}