{"id":"W4415495674","doi":"10.1029/2025ef006427","title":"Indigenous‐Led Nature‐Based Solutions Align Net‐Zero Emissions and Biodiversity Targets in Canada","year":2025,"lang":"en","type":"article","venue":"Earth s Future","topic":"Environmental Conservation and Management","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Assembly of First Nations; York University; Concordia University; Future Earth","funders":"Natural Sciences and Engineering Research Council of Canada; Concordia University; Microsoft","keywords":"Biodiversity; Indigenous; Government (linguistics); Climate change; Geospatial analysis; Scope (computer science); Traditional knowledge; Global biodiversity","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.001683859,0.0001670029,0.0002396542,0.0007310124,0.004183974,0.00205754,0.001119073,0.0004312671,0.003504384],"category_scores_gemma":[0.004882546,0.0001340141,0.0002925938,0.001779339,0.001060966,0.0006845884,0.001828958,0.0008782395,0.0001260249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09951289,"about_ca_system_score_gemma":0.1582479,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9971354,"about_ca_topic_score_gemma":0.9989273,"domain_scores_codex":[0.998349,0.0002276905,0.0000356741,0.0001389359,0.000474971,0.0007737774],"domain_scores_gemma":[0.9962097,0.0004278625,0.000240159,0.0001360097,0.001838689,0.001147497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001013574,0.001006724,0.6380712,0.000764546,0.0003532574,0.0007912542,0.02606644,0.02282471,0.004036333,0.07024922,0.04070199,0.1941207],"study_design_scores_gemma":[0.0001096461,0.0001779866,0.8645468,0.0002860817,0.0001678151,0.00007139611,0.03627703,0.01701617,0.001910237,0.004304513,0.07501789,0.000114399],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9658841,0.0005544439,0.001130326,0.003179022,0.00003400004,0.0001531365,0.001791835,0.00004502242,0.02722811],"genre_scores_gemma":[0.993226,0.0002672106,0.0009769039,0.0002403507,0.000003986251,0.00004394159,0.0004441826,0.00001051575,0.004786906],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09951289,"threshold_uncertainty_score":0.7220199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004075768290371967,"score_gpt":0.1784052114574966,"score_spread":0.1743294431671246,"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."}}