{"id":"W2580273847","doi":"10.1002/2016wr019813","title":"Quantifying streambed advection and conduction heat fluxes","year":2017,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Advection; Environmental science; Thermal conduction; Heat flux; Diel vertical migration; Hydrology (agriculture); Upwelling; Groundwater; Thermocline; Flux (metallurgy); Heat transfer; Geology; Mechanics; Climatology; Thermodynamics; Oceanography; Materials science; Physics; Geotechnical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0007854028,0.00006907726,0.00008372757,0.0000574104,0.002203284,0.0001591377,0.000200871,0.0000492076,0.0008228418],"category_scores_gemma":[0.0000697468,0.00004806598,0.00001526281,0.00003254979,0.0007419272,0.0002953855,0.0009229672,0.0001686977,0.0004788299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004493017,"about_ca_system_score_gemma":6.852089e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0017793,"about_ca_topic_score_gemma":0.003442171,"domain_scores_codex":[0.9989427,0.000109302,0.00008195487,0.0002768061,0.0002484737,0.0003407077],"domain_scores_gemma":[0.9996231,0.00003026581,0.00001456702,0.0002753807,0.00001014697,0.00004658583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006585575,0.00005193266,0.9594126,0.00003060948,0.00003276506,0.00001623716,0.003522051,0.00005272523,0.01997006,0.00004075213,0.01314843,0.003655934],"study_design_scores_gemma":[0.0002892703,0.0001238768,0.8817841,0.00001001768,0.000006504084,0.00000448952,0.0009087631,0.0002952813,0.008448061,0.0004642551,0.1075634,0.0001020376],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9633219,0.00001666417,0.000004942319,0.002340248,0.00007693248,0.0001678976,5.708846e-7,0.00002474591,0.03404613],"genre_scores_gemma":[0.9921767,0.0000889896,0.00003539972,0.00003871929,0.00004771684,0.00002861787,0.000002169151,0.000006598627,0.007575125],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09441494,"threshold_uncertainty_score":0.9990957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1078228416107706,"score_gpt":0.3607079910998803,"score_spread":0.2528851494891097,"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."}}