{"id":"W4411716971","doi":"10.1002/pan3.70049","title":"Co‐creating solutions to the hidden impacts of climate change on Canada's Pacific kelp forests","year":2025,"lang":"en","type":"article","venue":"People and Nature","topic":"Marine and coastal plant biology","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pacific Institute for Climate Solutions; Simon Fraser University","funders":"Marine Environmental Observation Prediction and Response Network; Pacific Institute for Climate Solutions","keywords":"Kelp; Kelp forest; Climate change; Indigenous; Geography; Global warming; Effects of global warming on oceans; Environmental science; Oceanography; Ecology; Psychological resilience; Biology; Geology","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":[0.003078188,0.0004593915,0.0002515746,0.001325324,0.009759795,0.005292875,0.001679476,0.001337832,0.006176047],"category_scores_gemma":[0.005098892,0.000215793,0.0004062655,0.001466676,0.003746328,0.002585447,0.008184739,0.002508887,0.0004146686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01882585,"about_ca_system_score_gemma":0.08568899,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6911435,"about_ca_topic_score_gemma":0.8948864,"domain_scores_codex":[0.9983543,0.0003511078,0.00003596842,0.0001937437,0.0003241025,0.0007408952],"domain_scores_gemma":[0.9952503,0.0005162677,0.0002896358,0.0003600924,0.001412436,0.002171188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002732016,0.0005427927,0.1422073,0.001442882,0.0004040004,0.002006636,0.06471653,0.006395505,0.009494744,0.036755,0.08629022,0.6494712],"study_design_scores_gemma":[0.00007992239,0.0003069488,0.1682881,0.001467683,0.0003833912,0.0003372675,0.2609516,0.009245436,0.004317316,0.03991671,0.5144931,0.0002125068],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6697944,0.008175288,0.01511459,0.1350279,0.001103841,0.0005962085,0.001200034,0.0006176168,0.1683701],"genre_scores_gemma":[0.9761971,0.002533706,0.008741044,0.003610425,0.00005779496,0.000128741,0.0001796731,0.00004074123,0.00851068],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3088565,"threshold_uncertainty_score":0.6213509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007907547529394899,"score_gpt":0.2176282800609902,"score_spread":0.2097207325315953,"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."}}