{"id":"W4210948361","doi":"10.1016/j.jglr.2022.01.021","title":"Characterizing stream planform geometry using a novel application of spectral analysis","year":2022,"lang":"en","type":"article","venue":"Journal of Great Lakes Research","topic":"Hydrology and Sediment Transport Processes","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Sinuosity; Curvature; Channel (broadcasting); Tributary; Geometry; Point (geometry); Planform; Inflection point; Window (computing); Mathematics; Hydrology (agriculture); Geology; Computer science; Geography; Cartography; Engineering; Telecommunications; Geotechnical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0002294249,0.0004875654,0.0003287447,0.001938263,0.0002879743,0.0008244076,0.0004300542,0.0003057014,0.001548527],"category_scores_gemma":[0.0008632828,0.0002132996,0.0004207392,0.001487906,0.000295771,0.0008559133,0.0006297715,0.0003358086,0.0006322282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001746797,"about_ca_system_score_gemma":0.0004376929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002949733,"about_ca_topic_score_gemma":0.006179736,"domain_scores_codex":[0.9997962,0.00003107392,0.000009153324,0.00005206459,0.00008938163,0.00002213317],"domain_scores_gemma":[0.999447,0.0001663475,0.00006580839,0.00009229595,0.0001961684,0.00003239074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002065394,0.0004837546,0.03567041,0.0001595226,0.0001734656,0.0001994023,0.0002963072,0.05070996,0.2642927,0.004424657,0.002567077,0.6408162],"study_design_scores_gemma":[0.00002862703,0.0001177231,0.02939122,0.00001539962,0.00006743837,0.000560418,0.0001837809,0.9323295,0.03188033,0.002387235,0.002980391,0.00005786503],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.22445,0.0001334361,0.7693718,0.0001071921,0.00005583676,0.00007468813,0.0006194258,0.001380645,0.003806858],"genre_scores_gemma":[0.575897,0.0002721184,0.4217602,0.00006156926,0.00006255119,0.00006848663,0.0006692825,0.0001717668,0.001037096],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002949733,"threshold_uncertainty_score":0.005865157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0434873819093364,"score_gpt":0.3231949553029377,"score_spread":0.2797075733936013,"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."}}