{"id":"W2891015662","doi":"10.1051/e3sconf/20184002031","title":"Geomorphic identification of physical habitat features in a large, altered river system","year":2018,"lang":"en","type":"article","venue":"E3S Web of Conferences","topic":"Hydrology and Sediment Transport Processes","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Habitat; Floodplain; Environmental science; STREAMS; Identification (biology); Hydrology (agriculture); Ecosystem; Environmental resource management; Geographic information system; Remote sensing; Ecology; Geography; Geology; Computer science; Cartography","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":[0.0002733928,0.0001562256,0.0001253784,0.0020619,0.0004619875,0.0007235163,0.0002533271,0.0001232225,0.0009237234],"category_scores_gemma":[0.0009397048,0.00008984736,0.00009538663,0.001348276,0.0003800611,0.000292303,0.0004035158,0.0001040327,0.0001256147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007650527,"about_ca_system_score_gemma":0.001106264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09951638,"about_ca_topic_score_gemma":0.4115507,"domain_scores_codex":[0.9998446,0.00003824741,0.00001289496,0.00002996971,0.00004737383,0.00002699988],"domain_scores_gemma":[0.9995165,0.00009208379,0.0001581409,0.00004518813,0.0001510038,0.00003710741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005151721,0.00003970863,0.8748761,0.00009354888,0.00002290733,0.0003098095,0.0009306422,0.005782919,0.01401717,0.00070717,0.0007522927,0.1024163],"study_design_scores_gemma":[0.000001932847,0.00002307606,0.9905491,0.00001007176,0.000008018058,0.0001379955,0.001045708,0.005692046,0.001325227,0.000146459,0.0010538,0.000006503961],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9785003,0.00009896851,0.01536377,0.00006014388,0.000003934467,0.0001248126,0.001443805,0.0001176648,0.004286541],"genre_scores_gemma":[0.9763033,0.00007106367,0.02232207,0.00001437451,0.000002846543,0.0000358282,0.0004952266,0.000008140139,0.000747174],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09951638,"threshold_uncertainty_score":0.1978743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009741792244533965,"score_gpt":0.2361882284311193,"score_spread":0.2264464361865853,"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."}}