{"id":"W3146370504","doi":"10.1038/s41559-021-01432-0","title":"A metric for spatially explicit contributions to science-based species targets","year":2021,"lang":"en","type":"article","venue":"Nature Ecology & Evolution","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":174,"is_retracted":false,"has_abstract":false,"ca_institutions":"Parks Canada","funders":"Agence Nationale de la Recherche; National Research Foundation; National Research Foundation Singapore; Newcastle University; Luc Hoffmann Institute; Global Environment Facility; Rufford Foundation","keywords":"Metric (unit); Computer science; Data science; Geography; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005231034,0.001045716,0.0009202417,0.005428632,0.0008185909,0.002644161,0.001120258,0.00150938,0.004494943],"category_scores_gemma":[0.04021798,0.0003555642,0.0005997302,0.004331006,0.001335686,0.004969636,0.004152194,0.001543221,0.001077059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001183736,"about_ca_system_score_gemma":0.0009159868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001291148,"about_ca_topic_score_gemma":0.002231389,"domain_scores_codex":[0.994108,0.002065923,0.0004786699,0.0007583953,0.002256849,0.0003321846],"domain_scores_gemma":[0.9742947,0.01268126,0.002817295,0.003705196,0.005106138,0.001395492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0009790402,0.0004257264,0.09239393,0.001101019,0.0009974268,0.0004594203,0.001269478,0.1986308,0.0142996,0.3510002,0.01940767,0.3190356],"study_design_scores_gemma":[0.0001144216,0.0006919596,0.08912671,0.0002645876,0.0004593296,0.00124559,0.001191013,0.2997597,0.009689197,0.5191381,0.07812721,0.0001922036],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2777487,0.003505638,0.6237602,0.003053611,0.0008191125,0.0002058649,0.008151779,0.001527151,0.08122794],"genre_scores_gemma":[0.8766804,0.0005680151,0.1157777,0.0001992813,0.0002661463,0.0002198375,0.002455335,0.0002164315,0.003616701],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005428632,"threshold_uncertainty_score":0.02766472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01083414399374512,"score_gpt":0.2751662000493759,"score_spread":0.2643320560556308,"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."}}