{"id":"W2804236052","doi":"","title":"Observing the Heterogeneity of Snow-Atmosphere Interactions over Wheat Stubble and Patchy Snowcover during Melt","year":2016,"lang":"en","type":"article","venue":"32nd Conf. on Agricultural and Forest Meteorology/22nd Symp. Boundary Layers and Turbulence/ Third Conf. on Atmospheric Biogeosciences (20 – 24 June, 2016)","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Atmosphere (unit); Snow; Environmental science; Atmospheric sciences; Meteorology; Geography; Geology","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":[0.0001933215,0.0002503986,0.0003668953,0.0005014373,0.0004098289,0.0004905451,0.0002602455,0.000341485,0.0009009144],"category_scores_gemma":[0.0004250748,0.0002704578,0.0002802313,0.0005451103,0.0001729481,0.0004681582,0.0005318715,0.0004203712,0.0002159264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002554342,"about_ca_system_score_gemma":0.0002555506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0127112,"about_ca_topic_score_gemma":0.03487279,"domain_scores_codex":[0.9999208,0.000007921984,0.000003121754,0.00002890042,0.000009253643,0.00002990242],"domain_scores_gemma":[0.9997855,0.00005311491,0.00004141484,0.00001947154,0.0000325983,0.00006793876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001072853,0.0002214829,0.8334078,0.00007403946,0.0003373956,0.0002313615,0.0007885298,0.007543732,0.1375477,0.000218956,0.001543222,0.0170131],"study_design_scores_gemma":[0.00001857633,0.00003153399,0.9903777,0.000003492411,0.00003270806,0.0000200707,0.0001422267,0.007927872,0.00112484,0.00006020099,0.0002541559,0.000006544057],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988195,0.00005480108,0.000228656,0.00002428905,0.000005926311,0.000002466908,0.0004163405,0.00002305356,0.0004247873],"genre_scores_gemma":[0.9991059,0.0000320759,0.0001787868,0.000008404423,0.000008242889,0.000003552526,0.0005478862,0.000008593429,0.0001065964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0127112,"threshold_uncertainty_score":0.0252744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0117950872023101,"score_gpt":0.204356267070966,"score_spread":0.1925611798686559,"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."}}