{"id":"W2921889800","doi":"10.1007/s11273-019-09655-6","title":"Hydrogeomorphic modeling of low-marsh habitat in coastal Georgian Bay, Lake Huron","year":2019,"lang":"en","type":"article","venue":"Wetlands Ecology and Management","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Marsh; Wetland; Habitat; Environmental science; Bay; Elevation (ballistics); Digital elevation model; Water level; Hydrology (agriculture); Georgian; Physical geography; Fishery; Oceanography; Ecology; Geography; Geology; Cartography; Remote sensing; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003522872,0.0001467223,0.0002567376,0.00008742757,0.00008350088,0.000006015104,0.0001582601,0.00008756772,0.00119958],"category_scores_gemma":[0.000007521947,0.0001432483,0.00003355945,0.0001358685,0.0001596399,0.0001171914,0.0007061669,0.0001078508,0.0002338905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003139432,"about_ca_system_score_gemma":0.000002559116,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003947999,"about_ca_topic_score_gemma":0.09216108,"domain_scores_codex":[0.9988891,0.0000505957,0.0002533544,0.0003628827,0.0001059406,0.0003381545],"domain_scores_gemma":[0.9996623,0.0000399847,0.00006970141,0.0001854318,0.000003974778,0.00003860165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005566755,0.0001369367,0.9843075,0.000115643,0.00005919901,0.00003464437,0.00009904064,0.01144879,0.00001410707,0.001861085,0.001655115,0.000212279],"study_design_scores_gemma":[0.001379985,0.0001759495,0.9779398,0.00002101461,0.00003414042,0.000002351822,0.0002369731,0.01575568,0.000005435049,0.001348355,0.002934702,0.0001655949],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9265852,0.000009523788,0.00007005176,0.0007593012,0.0001796756,0.0004972757,0.000004668583,0.00002057595,0.07187374],"genre_scores_gemma":[0.9967669,0.0002896821,0.0001318373,0.0007167644,0.00000692663,0.00005286321,0.00001679214,0.0000088099,0.002009398],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0921216,"threshold_uncertainty_score":0.9997135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005245522859355411,"score_gpt":0.1879860678140375,"score_spread":0.182740544954682,"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."}}