{"id":"W2526623122","doi":"10.1016/j.shpsc.2016.09.007","title":"AIC and the challenge of complexity: A case study from ecology","year":2016,"lang":"en","type":"article","venue":"Studies in History and Philosophy of Science Part C Studies in History and Philosophy of Biological and Biomedical Sciences","topic":"Philosophy and History of Science","field":"Arts and Humanities","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Michigan State University; National Science Foundation","keywords":"Simplicity; Akaike information criterion; Argument (complex analysis); Selection (genetic algorithm); Epistemology; Model selection; Computer science; Ecology; Philosophy; Artificial intelligence; Biology; Machine learning","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.003516734,0.0003143156,0.001150673,0.0004513547,0.0009629746,0.000006592478,0.000498208,0.00008996543,0.00007833083],"category_scores_gemma":[0.0006542748,0.0001584867,0.00007271304,0.0002484069,0.2710643,0.0003519453,0.0006563396,0.0002066179,5.093832e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001800558,"about_ca_system_score_gemma":0.0001015873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003931276,"about_ca_topic_score_gemma":0.0005130176,"domain_scores_codex":[0.9968989,0.0003512838,0.0009246396,0.0009214621,0.0005224457,0.0003812443],"domain_scores_gemma":[0.9971806,0.001820719,0.0004693377,0.0002137292,0.0001655576,0.0001499963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005802101,0.001006225,0.01115336,0.0004016747,0.0001484048,0.0001686197,0.2598407,1.899556e-7,0.0002743739,0.7212506,0.0002178591,0.004957799],"study_design_scores_gemma":[0.002557158,0.004554042,0.001628354,0.0006061995,0.00006637342,0.00005735694,0.03750586,0.00001317164,0.000009176615,0.9417921,0.01078312,0.0004270777],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8763402,0.1090679,3.014392e-7,0.0056143,0.001428363,0.0003784334,0.00004598224,0.00001018254,0.007114369],"genre_scores_gemma":[0.987644,0.01175989,0.00006057394,0.0002098814,0.000258175,0.00003790236,3.332048e-7,0.00000323558,0.0000260535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2701014,"threshold_uncertainty_score":0.7406519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3693315226636706,"score_gpt":0.3362966937385568,"score_spread":0.03303482892511378,"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."}}