{"id":"W2572261749","doi":"10.1016/j.jmarsys.2016.12.007","title":"Representing kelp forests in a tidal circulation model","year":2017,"lang":"en","type":"article","venue":"Journal of Marine Systems","topic":"Coastal wetland ecosystem dynamics","field":"Environmental Science","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bedford Institute of Oceanography; Fisheries and Oceans Canada","funders":"Government of Canada; Australian Government","keywords":"Kelp; Drag; Kelp forest; Drag coefficient; Dispersion (optics); Geology; Momentum (technical analysis); Atmospheric sciences; Physics; Mechanics; Ecology; Biology; Optics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0009842304,0.00008451724,0.0002173476,0.00006153585,0.0001145186,0.0001349373,0.0003438068,0.00004893591,0.00004151366],"category_scores_gemma":[0.000171561,0.00007145413,0.00007165397,0.00004498575,0.00002482897,0.0005069067,0.0004079518,0.0001454909,0.00002904769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002087561,"about_ca_system_score_gemma":0.00001413106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002464704,"about_ca_topic_score_gemma":0.006093139,"domain_scores_codex":[0.9987798,0.0000413448,0.0005248237,0.00012145,0.0003563926,0.0001762164],"domain_scores_gemma":[0.9987643,0.00002432871,0.0007834151,0.0003348522,0.00001943985,0.00007363466],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001487673,0.00001814597,0.761872,0.00002005891,0.000005018235,0.00003780763,0.0000556616,0.2363039,0.0002770054,0.000030179,0.0001025039,0.001262898],"study_design_scores_gemma":[0.0002630389,0.00001183824,0.503935,0.00004835435,0.000003675971,0.0001220827,0.00002233281,0.4952052,0.000002358327,0.0002623961,0.00007641645,0.00004728078],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9782808,0.000007284605,0.002425651,0.00009154386,0.0003822702,0.0001241471,0.00000107225,0.000004776073,0.01868239],"genre_scores_gemma":[0.9988001,0.000003729756,0.000221496,0.000003076637,0.000131417,0.000002163933,7.651681e-7,0.00001035389,0.000826875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2589014,"threshold_uncertainty_score":0.3725911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01585812568435468,"score_gpt":0.2472656297339391,"score_spread":0.2314075040495845,"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."}}