{"id":"W2316796933","doi":"10.4033/iee.2015.8.6.n","title":"Stoch-aptation: a new term in evolutionary biology and paleontology","year":2015,"lang":"en","type":"article","venue":"Ideas in Ecology and Evolution","topic":"Evolution and Paleontology Studies","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universidade da Coruña; Xunta de Galicia","keywords":"Term (time); Evolutionary biology; Biology; Selection (genetic algorithm); Paleontology; Biological evolution; Set (abstract data type); Ecology; Computer science; Artificial intelligence; Genetics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004153041,0.0001360422,0.0002629069,0.0002806499,0.0001078023,0.000006377912,0.00007496653,0.0002860828,0.0000735019],"category_scores_gemma":[0.000260534,0.0001307737,0.00001659505,0.0002108433,0.0004280683,0.0001824059,0.00002111392,0.0002159234,0.00004485183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003117347,"about_ca_system_score_gemma":0.0001497879,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003895917,"about_ca_topic_score_gemma":0.4727315,"domain_scores_codex":[0.9986948,0.0002773398,0.0002869602,0.0003363739,0.0000570452,0.0003475315],"domain_scores_gemma":[0.9994223,0.0002429064,0.00007296021,0.00008741521,0.00003554294,0.0001388372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001199147,0.00001614626,0.9904606,0.000005867741,0.000009755283,0.00001436018,0.0004853389,0.0001618102,0.00000263431,0.004953102,0.0004371318,0.003333353],"study_design_scores_gemma":[0.001219033,0.0002309179,0.9365962,0.00000852876,0.000008460763,0.0001338031,0.0004979337,0.002285688,1.257368e-7,0.05834479,0.0005451684,0.0001293961],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9767751,0.01520712,0.0002336858,0.002021572,0.0005932862,0.0001860655,0.000009310222,0.00002938724,0.004944544],"genre_scores_gemma":[0.998497,0.0002918875,0.0007095818,0.0002302274,0.00008468513,0.000006281862,0.00003186022,0.000001696233,0.0001467839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4688356,"threshold_uncertainty_score":0.5889487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02476441365688808,"score_gpt":0.2653550594197273,"score_spread":0.2405906457628392,"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."}}