{"id":"W4324082958","doi":"10.1101/2023.03.09.531893","title":"A social-ecological geography of southern Canadian Lakes","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Groupe de recherche interuniversitaire en limnologie; Fonds Québécois de la Recherche sur la Nature et les Technologies; Université de Sherbrooke","keywords":"Threatened species; Geography; Recreation; Ecology; Context (archaeology); Population; Watershed; Ecosystem; Ecosystem services; Lake ecosystem; Vulnerability (computing); Agriculture; Environmental resource management; Environmental science; Habitat","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":[0.0003296941,0.0002438531,0.0001893933,0.0034673,0.006038818,0.002353359,0.0006477448,0.00022024,0.00284133],"category_scores_gemma":[0.001033086,0.0001776753,0.0002235877,0.005433871,0.002841483,0.000505955,0.001709821,0.0002682712,0.00008314018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0443767,"about_ca_system_score_gemma":0.02814241,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9948572,"about_ca_topic_score_gemma":0.9979638,"domain_scores_codex":[0.9995015,0.00006685352,0.00001343644,0.00007108082,0.0001442902,0.0002027874],"domain_scores_gemma":[0.9991934,0.00006698447,0.0001372423,0.00002237762,0.0003836728,0.0001964284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009925415,0.00004860261,0.8295409,0.0001838217,0.0001241466,0.001030976,0.08011926,0.002983202,0.002517562,0.0266042,0.007327562,0.04942042],"study_design_scores_gemma":[0.000003204409,0.00001183698,0.9511305,0.00004297285,0.00001729522,0.00008856585,0.03361458,0.0009652245,0.00007441481,0.001009944,0.01301371,0.00002768839],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.975484,0.0004694193,0.0006273167,0.0008893947,0.000005816616,0.00007120102,0.001481236,0.00001896362,0.02095281],"genre_scores_gemma":[0.9978144,0.0001744237,0.0003553064,0.00003506206,0.000001651674,0.00001529877,0.000255012,0.000003006051,0.001345772],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0443767,"threshold_uncertainty_score":0.321977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01453257451555952,"score_gpt":0.2064027853244785,"score_spread":0.1918702108089189,"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."}}