{"id":"W4389101455","doi":"10.1016/j.pecon.2023.11.004","title":"Making the most of existing data in conservation research","year":2023,"lang":"en","type":"article","venue":"Perspectives in Ecology and Conservation","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; University of Ottawa; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; University of Ottawa; Environment and Climate Change Canada; Carleton University","keywords":"Data science; Computer science; Key (lock); Work (physics); Open data; Action (physics); Open research; Biodiversity conservation; Biodiversity; World Wide Web; Computer security; Engineering; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2958066,0.002659921,0.006981771,0.03158939,0.01188981,0.040583,0.0145841,0.01414252,0.02896192],"category_scores_gemma":[0.5422835,0.004503459,0.006079622,0.03503078,0.03470461,0.1131214,0.04137764,0.02521268,0.0166999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008374995,"about_ca_system_score_gemma":0.02969528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006513822,"about_ca_topic_score_gemma":0.00740573,"domain_scores_codex":[0.7348482,0.1690323,0.02937831,0.0197036,0.04347856,0.003559161],"domain_scores_gemma":[0.3012543,0.4070905,0.02461638,0.197068,0.05685192,0.01311884],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004942835,0.0003514865,0.009656657,0.01493907,0.001372851,0.0009674649,0.01644398,0.002031591,0.001975747,0.2183892,0.226889,0.5064887],"study_design_scores_gemma":[0.00006866214,0.00006757391,0.00177502,0.0207128,0.0003292275,0.000323683,0.005542474,0.0005408674,0.0008829802,0.3366202,0.632934,0.0002025504],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.005738667,0.08338483,0.2430384,0.5677195,0.02961354,0.001654342,0.01208968,0.00164099,0.05512001],"genre_scores_gemma":[0.1070883,0.1011402,0.5988775,0.129492,0.02594954,0.005171026,0.01677438,0.00407848,0.01142846],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7041934,"threshold_uncertainty_score":0.8683958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3737378852300295,"score_gpt":0.4398054375800389,"score_spread":0.06606755235000933,"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."}}