{"id":"W2778161391","doi":"10.1101/235705","title":"Biodiversity loss under future global socio-economic and climate scenarios","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Deutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-Leipzig","keywords":"Biodiversity; Geography; Deforestation (computer science); Climate change; Extinction (optical mineralogy); Land use; Habitat destruction; Global biodiversity; Arable land; Environmental resource management; Natural resource economics; Ecology; Agroforestry; Environmental science; Agriculture; Biology; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.0007760205,0.0004003173,0.0001873994,0.000974003,0.0002876518,0.001036692,0.0004091804,0.0004074772,0.002338791],"category_scores_gemma":[0.001533696,0.0001438944,0.0006527002,0.001490798,0.0004414086,0.001066243,0.001121995,0.0003880395,0.0003543873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001239129,"about_ca_system_score_gemma":0.0005065888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01229713,"about_ca_topic_score_gemma":0.01102183,"domain_scores_codex":[0.9996374,0.0001031945,0.00001895563,0.00004691764,0.0000986495,0.0000949524],"domain_scores_gemma":[0.9994909,0.00007604789,0.000186291,0.00006153792,0.0001191356,0.0000660759],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006010716,0.0001005642,0.6295266,0.0002901334,0.0008887051,0.0008408888,0.0004243264,0.3092929,0.003398127,0.00983381,0.007952047,0.03685087],"study_design_scores_gemma":[0.00005248443,0.0002736877,0.8158244,0.0001345449,0.000245658,0.0007201334,0.002274798,0.1460604,0.002459169,0.01494773,0.01690874,0.0000982696],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848319,0.0003401977,0.002409766,0.000626023,0.000037197,0.00001855123,0.004818615,0.0001037299,0.006813911],"genre_scores_gemma":[0.9972717,0.0001880604,0.0005986649,0.00005385692,0.000005963786,0.0000146478,0.001617817,0.000009854343,0.0002394311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01229713,"threshold_uncertainty_score":0.02445108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01707640209920675,"score_gpt":0.2226676247763735,"score_spread":0.2055912226771668,"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."}}