{"id":"W4367625677","doi":"10.29173/eureka28791","title":"Featuring Colleen St. Clair","year":2023,"lang":"en","type":"article","venue":"Eureka","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Women and Children’s Health Research Institute","funders":"","keywords":"Wildlife; Engineering; Human animal; Library science; Geography; Computer science; Biology; Ecology; Forestry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001358795,0.00004117142,0.00004009399,0.00001463569,0.0001156651,0.000007033633,0.00008854126,0.00003911459,0.002573851],"category_scores_gemma":[0.00003473638,0.00003961353,0.00001458535,0.0003576275,0.00003747185,0.00007355506,0.00008116359,0.0000616641,0.00572945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003345145,"about_ca_system_score_gemma":0.00000560684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001759649,"about_ca_topic_score_gemma":0.0001769937,"domain_scores_codex":[0.9995739,0.00002167965,0.00005432928,0.0001191516,0.00008094001,0.0001499469],"domain_scores_gemma":[0.9998239,0.00003225044,0.00001673567,0.00009362155,0.00000190194,0.00003159701],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003313986,0.000008007546,0.6665618,9.711158e-7,0.000002548925,0.000009994031,0.00009472514,0.0002090392,0.000148621,0.00007863364,0.3319385,0.0009438448],"study_design_scores_gemma":[0.00008101985,0.00001357228,0.8559529,0.000001444171,0.000001883528,0.000001461304,0.00002367742,0.000254377,0.00006731085,0.0003582122,0.1431992,0.00004488196],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9691023,0.000004681066,0.00001347138,0.002969622,0.0001854727,0.00006793645,0.000001750807,0.0001298739,0.02752492],"genre_scores_gemma":[0.9626545,0.000008576553,0.0001468673,0.0009221368,0.00006085366,0.00001584913,0.00001796188,0.000007158333,0.03616614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1893911,"threshold_uncertainty_score":0.9983379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01206129282776014,"score_gpt":0.2167270266710389,"score_spread":0.2046657338432788,"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."}}