{"id":"W4409859012","doi":"10.1002/hyp.70135","title":"Snow Interception Relationships With Meteorology and Canopy Density","year":2025,"lang":"en","type":"article","venue":"Hydrological Processes","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Global Water Futures; Alberta Innovates; Canada First Research Excellence Fund; Canada Research Chairs; Environment and Climate Change Canada; Canada Foundation for Innovation; University of Saskatchewan","keywords":"Snow; Interception; Environmental science; Meteorology; Canopy; Atmospheric sciences; Climatology; Geography; 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":[0.0002102015,0.000250276,0.0001778882,0.0004064838,0.0002657999,0.00060814,0.0003148468,0.000137211,0.0006156919],"category_scores_gemma":[0.0008359441,0.0001407569,0.000189337,0.0003948761,0.0002182408,0.0001675601,0.000167371,0.0001353342,0.0000885461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001607369,"about_ca_system_score_gemma":0.0008119533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4832567,"about_ca_topic_score_gemma":0.5128039,"domain_scores_codex":[0.9998884,0.000009036748,0.000004961741,0.00003121268,0.00003978961,0.00002645615],"domain_scores_gemma":[0.9996588,0.0001164143,0.00006794855,0.00002335161,0.00009815564,0.00003534702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009037765,0.00002792537,0.962258,0.00002777123,0.00006154527,0.00006037756,0.0001556415,0.01385022,0.01551462,0.0001049562,0.0001063055,0.007742223],"study_design_scores_gemma":[0.000001620718,0.00001475656,0.9889684,0.000001897929,0.000006756225,0.00002404325,0.00006236583,0.009927026,0.0008449269,0.00003575959,0.0001084447,0.000003980213],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981524,0.00003545021,0.001081697,0.000004962228,6.055092e-7,0.000009211634,0.0002081507,0.0000307372,0.00047673],"genre_scores_gemma":[0.9993625,0.00001357574,0.0003450379,0.000001137456,2.958882e-7,0.000002412522,0.0001658774,0.000002538109,0.0001066494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4832567,"threshold_uncertainty_score":0.9608877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03007264940030545,"score_gpt":0.225990280129615,"score_spread":0.1959176307293096,"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."}}