{"id":"W2255050781","doi":"10.1002/wat2.1135","title":"A practitioner's guide to thermal infrared remote sensing of rivers and streams: recent advances, precautions and considerations","year":2016,"lang":"en","type":"article","venue":"Wiley Interdisciplinary Reviews Water","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Fluvial; Remote sensing; Environmental science; Temporal scales; STREAMS; Scale (ratio); Thermal infrared; Climate change; Habitat; Environmental resource management; Hydrology (agriculture); River ecosystem; Computer science; Ecology; Geography; Geology; Infrared; Cartography; Geomorphology","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":[0.005676094,0.002296679,0.002033167,0.006530037,0.0009138989,0.0030397,0.004001638,0.006280804,0.03146696],"category_scores_gemma":[0.01730711,0.001346215,0.001502567,0.005193776,0.002503417,0.005403455,0.002801814,0.008086261,0.04569837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001110488,"about_ca_system_score_gemma":0.002735537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004934697,"about_ca_topic_score_gemma":0.00722854,"domain_scores_codex":[0.9968691,0.0008206012,0.0005734549,0.0003939096,0.001230415,0.0001124068],"domain_scores_gemma":[0.9861124,0.00670468,0.0006371436,0.0007882411,0.005270412,0.0004870986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000370513,0.0001081269,0.0006602001,0.002668879,0.00002888132,0.0004724814,0.0002876427,0.000806457,0.001788995,0.005553582,0.5252816,0.462306],"study_design_scores_gemma":[0.00000657919,0.00005239316,0.0007179574,0.001881734,0.00001277759,0.00175794,0.0001698821,0.0004587766,0.0002115199,0.007580004,0.9871079,0.0000424659],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.001141739,0.5579801,0.245048,0.07396228,0.03499,0.001256419,0.004202782,0.004478807,0.07693992],"genre_scores_gemma":[0.006809346,0.5390003,0.3022478,0.04314425,0.0212488,0.001848615,0.004185196,0.001734969,0.07978071],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.03146696,"threshold_uncertainty_score":0.1052675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01545401947694749,"score_gpt":0.2834059953252316,"score_spread":0.2679519758482842,"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."}}