{"id":"W4293085477","doi":"10.3390/geosciences12040142","title":"Mapping Underwater Bathymetry of a Shallow River from Satellite Multispectral Imagery","year":2022,"lang":"en","type":"article","venue":"Geosciences","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Remote sensing; Multispectral image; Bathymetry; Underwater; Satellite; Satellite imagery; Geology; Channel (broadcasting); Environmental science; Computer science; Oceanography; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.00007200033,0.0002563912,0.00009259827,0.0008719937,0.0001277667,0.0002491282,0.0001470639,0.000140294,0.0007470314],"category_scores_gemma":[0.0001507034,0.0001121593,0.0001321213,0.0006132004,0.0001083409,0.000194238,0.0001961742,0.0001110672,0.0002612638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000253251,"about_ca_system_score_gemma":0.0004963701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05807816,"about_ca_topic_score_gemma":0.1464635,"domain_scores_codex":[0.999945,0.000004091208,0.000002032376,0.0000110316,0.00002632066,0.00001148006],"domain_scores_gemma":[0.9999534,0.000005102745,0.000008209493,0.000005497178,0.00002101312,0.000006846336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00008825017,0.00008190969,0.109809,0.0002097673,0.00005025207,0.0007234181,0.0007067838,0.02095348,0.6015145,0.000636326,0.002291203,0.2629352],"study_design_scores_gemma":[0.00001084117,0.00007549736,0.7956701,0.00004845198,0.00005708195,0.000589334,0.001155299,0.151343,0.04660338,0.0002601505,0.004140808,0.00004608262],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9610082,0.000155411,0.032065,0.0000456425,0.000007889758,0.00004143047,0.001110241,0.0003973608,0.00516878],"genre_scores_gemma":[0.9568872,0.0002015907,0.04017381,0.00001958046,0.000004233381,0.00002096546,0.0009257072,0.00003200045,0.001734979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05807816,"threshold_uncertainty_score":0.1154802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267357809435321,"score_gpt":0.2179434631554284,"score_spread":0.2052698850610752,"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."}}