{"id":"W3127413172","doi":"10.1029/2020wr028712","title":"Predicting Latent and Sensible Heat Fluxes in Stream Temperature Models: Current Challenges and Potential Solutions","year":2021,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University; Natural Resources Canada; Canadian Forest Service; University of British Columbia","funders":"","keywords":"Sensible heat; Latent heat; Environmental science; Evaporation; Current (fluid); Heat flux; Meteorology; Wind speed; Atmospheric sciences; Heat transfer; Climatology; Thermodynamics; Geology; Geography; Physics","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":[0.01426493,0.001464173,0.003035544,0.0009239462,0.0008817788,0.005148325,0.004187074,0.004992423,0.002402254],"category_scores_gemma":[0.03571922,0.0015236,0.001565534,0.001581513,0.002705151,0.008197581,0.003315664,0.004385076,0.0007632839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001385215,"about_ca_system_score_gemma":0.00419456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01906203,"about_ca_topic_score_gemma":0.01187416,"domain_scores_codex":[0.9965723,0.001753242,0.000312635,0.0007128598,0.0005011464,0.0001478137],"domain_scores_gemma":[0.9726303,0.02026276,0.001049756,0.001360981,0.003976692,0.0007194814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001992968,0.0002618675,0.01080889,0.001781681,0.0003636045,0.00009200886,0.0002219342,0.7771124,0.001355372,0.02509324,0.008814646,0.1738951],"study_design_scores_gemma":[0.00003973111,0.00006171571,0.001193295,0.0004161948,0.00004218543,0.00001941399,0.0002789605,0.9546774,0.0005370357,0.03510175,0.007553832,0.00007839948],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09114712,0.1555443,0.6267747,0.1099393,0.00308157,0.000327855,0.001709498,0.003129505,0.008346119],"genre_scores_gemma":[0.6129893,0.07648804,0.2972575,0.00234732,0.00528066,0.000777269,0.001781636,0.0005243469,0.002553861],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01906203,"threshold_uncertainty_score":0.07544106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0620310614278919,"score_gpt":0.2830343283078708,"score_spread":0.221003266879979,"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."}}