{"id":"W3046993485","doi":"","title":"Investigating the spring snow melt signal in soil moisture data from the Cariboo Mountains, British Columbia","year":2009,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Spring (device); Snow; Snowmelt; Environmental science; Moisture; Hydrology (agriculture); Water content; Physical geography; Geology; Remote sensing; Geography; Meteorology; Engineering; Geotechnical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003400134,0.000167145,0.0002292014,0.001305738,0.001538462,0.001093831,0.0004470556,0.000333891,0.000954261],"category_scores_gemma":[0.001645867,0.0001723711,0.0001168923,0.002853271,0.0002942196,0.0002421095,0.0006149966,0.0003422644,0.0001929234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003301788,"about_ca_system_score_gemma":0.005470061,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9715232,"about_ca_topic_score_gemma":0.9918398,"domain_scores_codex":[0.99977,0.00003326185,0.00001635454,0.00004564729,0.00005495795,0.00007981478],"domain_scores_gemma":[0.9990029,0.0001712503,0.00008448948,0.0000498075,0.0005513054,0.000140344],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001468569,0.00006381325,0.9716071,0.00003465746,0.0000790565,0.0002864541,0.001463693,0.001318727,0.005879786,0.0001159857,0.001843924,0.01716],"study_design_scores_gemma":[0.000007449401,0.000004994094,0.9955164,0.00001207045,0.00001745815,0.00002511518,0.001129439,0.001614109,0.000299669,0.00001591147,0.001351203,0.000006267021],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978716,0.00009100846,0.00006308483,0.00006621682,0.000003149642,0.000005637804,0.0008360735,0.00001060808,0.001052643],"genre_scores_gemma":[0.9975291,0.00008181039,0.0001427211,0.00002804342,0.000002491278,0.000006165389,0.001252759,0.000007077597,0.0009499249],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02847683,"threshold_uncertainty_score":0.057289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04348176446012515,"score_gpt":0.2395100883297023,"score_spread":0.1960283238695771,"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."}}