{"id":"W2170985466","doi":"10.1655/0733-1347(2007)20[83:psarco]2.0.co;2","title":"POPULATION SIZE AND RECOVERY CRITERIA OF THE THREATENED LAKE ERIE WATERSNAKE: INTEGRATING MULTIPLE METHODS OF POPULATION ESTIMATION","year":2006,"lang":"en","type":"article","venue":"Herpetological Monographs","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Threatened species; Endangered species; Mark and recapture; Population size; Statistics; Population; Point estimation; Range (aeronautics); Estimation; Vital rates; Biology; Population viability analysis; Confidence interval; Sample size determination; Ecology; Demography; Geography; Mathematics; Population growth; Habitat","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003116988,0.00009920162,0.0001992277,0.00002516969,0.0001392464,0.000007999089,0.00008149604,0.00008372815,0.0002477094],"category_scores_gemma":[0.0002698856,0.00006192196,0.00006270054,0.0001963763,0.0001969393,0.0001423378,0.0001390223,0.00005938762,9.479394e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001428661,"about_ca_system_score_gemma":5.434787e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005670663,"about_ca_topic_score_gemma":0.006953095,"domain_scores_codex":[0.9991124,0.0001948633,0.0003013307,0.0001812837,0.00008755545,0.0001225375],"domain_scores_gemma":[0.9994124,0.0002556994,0.0001897118,0.0001212866,0.000008062367,0.00001285325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003662201,0.00004724962,0.9906853,0.00001550009,0.00001108205,2.877562e-7,0.000049932,0.000844196,0.001326431,0.0003278129,0.0002472636,0.006408332],"study_design_scores_gemma":[0.0001584054,0.00006567263,0.9725206,0.00001219316,0.00002552532,8.89205e-7,0.00004643042,0.003232858,0.0004374307,0.02333421,0.00009875129,0.00006697575],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956153,0.00001599517,0.002307117,0.0002265029,0.00009306554,0.0002334898,0.000009711223,0.00002477166,0.001474055],"genre_scores_gemma":[0.9517631,0.00001186748,0.04806307,0.00006224622,0.00000486619,0.00001903073,0.00002910086,0.000003805489,0.00004290194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04575595,"threshold_uncertainty_score":0.387999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01136584795912005,"score_gpt":0.2652129238734109,"score_spread":0.2538470759142909,"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."}}