{"id":"W4220909137","doi":"10.5751/es-13006-270141","title":"Murky waters: divergent ways scientists, practitioners, and landowners evaluate beaver mimicry","year":2022,"lang":"en","type":"article","venue":"Ecology and Society","topic":"Ecology and biodiversity studies","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Nature Conservancy; U.S. Geological Survey; Montana State University","keywords":"Mimicry; Salience (neuroscience); Beaver; Legitimacy; Credibility; Natural resource management; Popularity; Natural resource; Public relations; Environmental resource management; Environmental ethics; Political science; Ecology; Psychology; Social psychology; Biology","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":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004855664,0.00007980784,0.0001040202,0.00001037464,0.002011059,0.00001012503,0.00008049313,0.00005998574,0.002024216],"category_scores_gemma":[0.00001247277,0.00006993211,0.00004582315,0.00006806265,0.0006531462,0.0001076094,0.0008876915,0.0001654102,0.00008651136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001113317,"about_ca_system_score_gemma":0.000007631575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000501464,"about_ca_topic_score_gemma":0.00005972186,"domain_scores_codex":[0.9992465,0.0000816891,0.00007357075,0.0002758481,0.0001088984,0.0002134626],"domain_scores_gemma":[0.9997746,0.00006246121,0.00004357847,0.00006383086,0.000004752214,0.0000507921],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001625737,0.00006325624,0.8299051,0.000004099234,0.00006186627,0.000009434007,0.003802531,0.00004019371,0.0002164213,0.0000882347,0.1656836,0.0001090418],"study_design_scores_gemma":[0.0006692445,0.0001400934,0.9322267,5.542369e-7,0.00005598115,0.00002477619,0.00372177,0.0001131646,0.00002995123,0.0004981461,0.06239182,0.0001278539],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995414,0.00007899699,0.000005857065,0.00261784,0.0003405655,0.000126888,0.00003243927,0.00001967961,0.001363792],"genre_scores_gemma":[0.9950517,0.0004219399,0.0004148357,0.002482841,0.00001407686,0.00002051418,0.00002235556,0.000002424574,0.001569316],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1032917,"threshold_uncertainty_score":0.9992882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01471219668033508,"score_gpt":0.2126784619844409,"score_spread":0.1979662653041058,"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."}}