{"id":"W2953651188","doi":"","title":"Capturing nuisance urban Canada geese using the bird immobilizing agent alpha-chloralose in Reno, Nevada: What we learned","year":2004,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Department of Agriculture","keywords":"Wildlife; Goose; Alpha (finance); Environmental science; Fishery; Geography; Ecology; Business; Service (business); Biology; Marketing","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0002034875,0.0002741175,0.0001860845,0.00008690134,0.0002281613,0.001159534,0.000561106,0.0001443199,0.00004626079],"category_scores_gemma":[0.0001652221,0.0002372918,0.0001132397,0.0003794205,0.000118563,0.0003004067,0.000202309,0.0003300146,0.0001089236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001146453,"about_ca_system_score_gemma":0.0005763842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002591417,"about_ca_topic_score_gemma":0.00726858,"domain_scores_codex":[0.99806,0.00009110447,0.0005179484,0.0005840007,0.000308647,0.0004382333],"domain_scores_gemma":[0.9988659,0.00002694333,0.0001901243,0.000692658,0.00005273729,0.0001716492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001322504,0.001972027,0.2057196,0.0006281189,0.0006128435,0.0003129509,0.001329107,0.012848,0.7188434,0.01112686,0.01917781,0.0261068],"study_design_scores_gemma":[0.001784434,0.00009088897,0.00758941,0.0004098555,0.00002961136,0.00005492837,0.001689924,0.0001958106,0.430932,0.00158366,0.5545112,0.001128164],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921936,0.003192437,0.0002044958,0.003053389,0.0003961444,0.0003538053,0.0001881343,0.00006965317,0.0003483275],"genre_scores_gemma":[0.9973894,0.0003239686,0.0002235189,0.0008149655,0.0001744753,0.00002902215,0.0003700626,0.00008671915,0.0005879105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5353335,"threshold_uncertainty_score":0.9998773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02836556047375263,"score_gpt":0.241827645348951,"score_spread":0.2134620848751984,"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."}}