{"id":"W3013501180","doi":"10.1007/s10811-020-02084-6","title":"Predicting distributional shifts of commercially important seaweed species in the Subantarctic tip of South America under future environmental changes","year":2020,"lang":"en","type":"article","venue":"Journal of Applied Phycology","topic":"Marine and coastal plant biology","field":"Earth and Planetary Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"Fondo Nacional de Desarrollo Científico y Tecnológico","keywords":"Species richness; Habitat; Species distribution; Ecology; Biodiversity; Climate change; Range (aeronautics); Temperate climate; Ecosystem; Environmental science; Geography; Biology","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":[0.0002045681,0.0001499293,0.0001174772,0.0008472452,0.0003522169,0.0005069929,0.0002733959,0.0002632366,0.00113622],"category_scores_gemma":[0.0008424922,0.0001196191,0.0002683268,0.0009747201,0.0002599972,0.0005059962,0.0004313905,0.0002412075,0.0001480124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009206395,"about_ca_system_score_gemma":0.0004878718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09523365,"about_ca_topic_score_gemma":0.2118828,"domain_scores_codex":[0.9999309,0.00001526021,0.000005258859,0.00002287157,0.000008760224,0.00001701354],"domain_scores_gemma":[0.9996135,0.0001089768,0.0001041869,0.00001770602,0.00008565285,0.00006999895],"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":[0.00003720857,0.00001381447,0.9912536,0.00001144715,0.00003306553,0.00007843007,0.000300916,0.003211171,0.001359545,0.0000799656,0.0001347624,0.003486105],"study_design_scores_gemma":[0.000003112831,0.00001087791,0.9905591,0.000005151324,0.00001071873,0.00004818105,0.001297953,0.007584474,0.0001049897,0.00007360619,0.0002985557,0.000003307239],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9994326,0.00002282995,0.00008086229,0.00003462032,8.398193e-7,0.000001813185,0.0001503312,0.000002391606,0.0002737765],"genre_scores_gemma":[0.9994659,0.00003521729,0.0001546064,0.000008605122,0.000001232474,0.000003076742,0.0002324978,0.000001406098,0.00009762535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09523365,"threshold_uncertainty_score":0.1893587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01375064979504412,"score_gpt":0.1848881941460852,"score_spread":0.1711375443510411,"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."}}