{"id":"W3045091212","doi":"10.1111/csp2.218","title":"Research–management partnerships: An opportunity to integrate genetics in conservation actions","year":2020,"lang":"en","type":"article","venue":"Conservation Science and Practice","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Conservation genetics; Legislation; Genetic diversity; Government (linguistics); Diversity (politics); Conservation biology; Business; Biodiversity conservation; Environmental resource management; Knowledge management; Political science; Biology; Biodiversity; Sociology; Ecology; Population; Computer science; Genetics; Economics","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":[0.003599072,0.00009439899,0.00008308997,0.0001088186,0.0005837542,0.000146475,0.0003365129,0.00003381897,0.0002078621],"category_scores_gemma":[0.003401283,0.00009748072,0.000008505058,0.001782108,0.001034503,0.001995963,0.0005450399,0.0002017462,0.0003115757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002650958,"about_ca_system_score_gemma":0.00004213399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005633667,"about_ca_topic_score_gemma":0.0003515212,"domain_scores_codex":[0.9979039,0.0003113925,0.000183367,0.0004923916,0.0008302395,0.0002787007],"domain_scores_gemma":[0.998795,0.0003807441,0.00007167141,0.0002147033,0.00008142315,0.0004564664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004090609,0.0004151788,0.8371798,0.00002896705,0.00001952579,0.00005995869,0.02726163,0.0005167921,0.03699024,0.002542873,0.04845861,0.04611729],"study_design_scores_gemma":[0.000286923,0.0002705295,0.6282944,0.00001382032,0.00001662279,0.000005808992,0.06075319,0.00262788,0.001112756,0.0001877153,0.3062136,0.0002167674],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8746331,0.00001379942,0.0002035555,0.1117799,0.00004853164,0.0004374408,0.000005105893,0.00002618032,0.0128524],"genre_scores_gemma":[0.9467582,0.000269448,0.01481062,0.03798981,0.00001593302,0.00003168326,0.00000513603,0.000005060951,0.0001141161],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.257755,"threshold_uncertainty_score":0.4489824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4675310859043889,"score_gpt":0.4183020266303157,"score_spread":0.04922905927407323,"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."}}