{"id":"W4411638594","doi":"10.1016/j.tree.2025.04.010","title":"No species left behind: borrowing strength to map data-deficient species","year":2025,"lang":"en","type":"review","venue":"Trends in Ecology & Evolution","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; Memorial University of Newfoundland; McGill University","funders":"Yale University; E.O. Wilson Biodiversity Foundation","keywords":"Biodiversity; Global biodiversity; Species distribution; Environmental niche modelling; Spatial analysis; Closing (real estate); Ecology; Distribution (mathematics); Niche; Data science; Environmental resource management; Biology; Computer science; Geography; Ecological niche; Habitat; Business; Remote sensing; Economics","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":[0.00251853,0.001162927,0.001397444,0.00369088,0.0003786083,0.002125522,0.002377348,0.001189951,0.003804274],"category_scores_gemma":[0.007262248,0.0004342129,0.001161055,0.004306071,0.001385774,0.004613987,0.001530545,0.001548007,0.001719983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007990657,"about_ca_system_score_gemma":0.002010686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005418678,"about_ca_topic_score_gemma":0.007878283,"domain_scores_codex":[0.9993529,0.0002036695,0.00005949826,0.0001683844,0.0001799913,0.00003558707],"domain_scores_gemma":[0.9973622,0.001728899,0.0002504407,0.000203282,0.0003881158,0.00006720461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002424932,0.00001479919,0.001736711,0.01138149,0.0002636562,0.00007187737,0.0001745225,0.002399596,0.0003727009,0.02124176,0.01451024,0.9478083],"study_design_scores_gemma":[0.00001539299,0.00007679279,0.007553957,0.01873345,0.0005997058,0.0009773739,0.000688081,0.004264662,0.0008836972,0.08763289,0.8784496,0.0001243858],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002026577,0.9472986,0.03645412,0.003970113,0.0009087923,0.00004413172,0.0009288206,0.0002615011,0.008107288],"genre_scores_gemma":[0.01732676,0.9538915,0.02490843,0.001090627,0.0003732887,0.00007175008,0.0009378269,0.00008525726,0.001314531],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005418678,"threshold_uncertainty_score":0.01331943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06667499072021332,"score_gpt":0.3327070783283028,"score_spread":0.2660320876080894,"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."}}