{"id":"W4387114617","doi":"10.1111/cobi.14192","title":"Lessons from COP15 on effective scientific engagement in biodiversity policy processes","year":2023,"lang":"en","type":"article","venue":"Conservation Biology","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wildlife Conservation Society Canada","funders":"Wilburforce Foundation","keywords":"Convention on Biological Diversity; Negotiation; Biodiversity; Context (archaeology); Nexus (standard); Science policy; Framing (construction); Political science; Environmental resource management; Environmental planning; Geography; Ecology; Biology; Computer science; Public administration; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002640371,0.00007206107,0.00008180564,0.0001014743,0.0001979875,0.0000256507,0.0001331737,0.00005933665,0.005908987],"category_scores_gemma":[0.0003823167,0.00006771155,0.00001724137,0.001103512,0.0002768169,0.00006120816,0.0001446868,0.00006711692,0.005175967],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003763429,"about_ca_system_score_gemma":0.0000263409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002238276,"about_ca_topic_score_gemma":0.00316616,"domain_scores_codex":[0.9992439,0.0001056175,0.00009281687,0.0002905031,0.00008144821,0.0001857064],"domain_scores_gemma":[0.9995777,0.0001992663,0.00004472781,0.0001257163,0.0000164363,0.00003613966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000361682,0.00009394001,0.9023951,0.000007703045,0.000006528416,0.000003804506,0.0007137422,0.00001916764,0.01512818,0.003367587,0.07596295,0.002265077],"study_design_scores_gemma":[0.0003048474,0.00003761091,0.8655279,0.000004735592,0.000001949159,1.135604e-7,0.0005250149,0.00003730202,0.002623025,0.0007346991,0.1301295,0.00007328013],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9827987,0.000008189854,0.00001341803,0.01318002,0.0001790656,0.0002124967,0.0003694189,0.00007380069,0.003164894],"genre_scores_gemma":[0.9968328,0.00003413004,0.00000577011,0.001950806,0.00001321738,0.00004319624,0.0009320594,0.000002039723,0.0001860035],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05416654,"threshold_uncertainty_score":0.9955986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08752964217206158,"score_gpt":0.3227822851451594,"score_spread":0.2352526429730979,"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."}}