{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.133394,0.0009430193,0.00131938,0.002422843,0.022951,0.03292091,0.005124099,0.02019578,0.02010121],"category_scores_gemma":[0.122213,0.000913666,0.001795972,0.002619792,0.07404879,0.02363971,0.03774633,0.01740195,0.002462388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04824987,"about_ca_system_score_gemma":0.1022798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1161308,"about_ca_topic_score_gemma":0.09263788,"domain_scores_codex":[0.9016232,0.06123528,0.002786788,0.005704292,0.01019957,0.01845081],"domain_scores_gemma":[0.8549687,0.09265111,0.00523492,0.01003001,0.01746706,0.01964825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00007019324,0.00009972579,0.002339937,0.0003234516,0.00004855197,0.0005971359,0.03415027,0.001365251,0.0002550189,0.8848287,0.04137129,0.03455052],"study_design_scores_gemma":[0.00008007847,0.00007249184,0.003886262,0.00152825,0.00002637086,0.0001539697,0.02945421,0.001031199,0.0004564321,0.6469622,0.3162687,0.00007979671],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02139215,0.006013362,0.01689365,0.6039774,0.001661473,0.0003773282,0.0001788101,0.0001146676,0.3493911],"genre_scores_gemma":[0.8277598,0.003448349,0.01791967,0.1280466,0.001547032,0.001458553,0.0001751273,0.0003539686,0.01929088],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.977049,"threshold_uncertainty_score":0.7054632,"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."}}