{"id":"W2082845746","doi":"10.1890/0012-9658(2001)082[1191:ciftoi]2.0.co;2","title":"CONFIDENCE INTERVALS FOR THE OPTIMUM IN THE GAUSSIAN RESPONSE FUNCTION","year":2001,"lang":"en","type":"article","venue":"Ecology","topic":"Control Systems and Identification","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Confidence interval; Statistics; Function (biology); Ecology; Gaussian; Mathematics; Environmental science; Biology; Evolutionary biology; Physics","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":[0.0008495018,0.0000405309,0.00006173611,0.00003330987,0.00004810685,0.00002519345,0.0001138256,0.00003979085,0.00006317606],"category_scores_gemma":[0.0001052423,0.00002491323,0.00002610769,0.00006791444,0.00001378632,0.00004287082,0.000005181122,0.00005782091,0.00004835531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003130842,"about_ca_system_score_gemma":0.000006468416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003291224,"about_ca_topic_score_gemma":0.001124674,"domain_scores_codex":[0.9995812,0.00008851901,0.0001303221,0.00006456926,0.00002975221,0.0001056723],"domain_scores_gemma":[0.9992696,0.0005352161,0.00001917221,0.0001537133,0.00001476271,0.000007518353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.008096022,0.0003897376,0.03152456,0.0002817918,0.0006104616,0.00008033654,0.02294725,0.1593957,0.1645369,0.1299245,0.3523237,0.1298891],"study_design_scores_gemma":[0.0006008253,0.0001386462,0.7151201,0.00000969905,0.00001927484,0.00002799487,0.0007442329,0.08221504,0.0000592895,0.001802514,0.1991786,0.00008372206],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.872742,0.0007929907,0.1078447,0.0117336,0.003145501,0.001367414,0.00000432554,0.0001038305,0.00226563],"genre_scores_gemma":[0.9987901,0.00001997768,0.000009796737,0.0001564268,0.0001020345,0.0002485539,0.000001463468,0.000005326718,0.0006662547],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6835956,"threshold_uncertainty_score":0.1015932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01651413510514245,"score_gpt":0.2444095293411997,"score_spread":0.2278953942360572,"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."}}