{"id":"W6930834077","doi":"10.5281/zenodo.15007098","title":"Implementing a plant hydraulics parameterization in the Canadian Land Surface Scheme Including biogeochemical Cycles (CLASSIC) v.1.4","year":2025,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Face Recognition and Perception","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Biogeochemical cycle; Hydraulics; Boreal; Hydrology (agriculture); Xylem; Hydrogeology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.000782637,0.0053015,0.001701481,0.002750443,0.001433688,0.002162648,0.005945887,0.002643202,0.01839334],"category_scores_gemma":[0.002942698,0.001138808,0.002434842,0.004327237,0.0007821759,0.001052832,0.001780443,0.002582721,0.03565149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005919576,"about_ca_system_score_gemma":0.007479847,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5483303,"about_ca_topic_score_gemma":0.7196376,"domain_scores_codex":[0.9991385,0.00006502043,0.00004048083,0.0002496387,0.0003172168,0.000189137],"domain_scores_gemma":[0.9990982,0.000112125,0.00004416106,0.0002849278,0.0003666327,0.00009403253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001183999,0.00008438388,0.002434554,0.0006025459,0.0001428335,0.00007179635,0.0000355437,0.00594493,0.0006595755,0.0009351854,0.9795979,0.009372425],"study_design_scores_gemma":[0.0006690256,0.000053998,0.01939292,0.0003124111,0.0001351621,0.0002050987,0.0001549857,0.02803821,0.003667285,0.005525818,0.9416621,0.0001830515],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002415168,0.0003422684,0.001193707,0.0001346485,0.00006889994,0.00006383649,0.986265,0.00709447,0.002422021],"genre_scores_gemma":[0.002207251,0.00009591816,0.002037473,0.00005198613,0.000005474231,0.00007763171,0.9942629,0.0002352685,0.001026049],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4516697,"threshold_uncertainty_score":0.9086593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09846874061934092,"score_gpt":0.3073980352071085,"score_spread":0.2089292945877676,"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."}}