{"id":"W3108377418","doi":"10.1175/jtech-d-20-0185.1","title":"FOWD: A Free Ocean Wave Dataset for Data Mining and Machine Learning","year":2021,"lang":"en","type":"article","venue":"Journal of Atmospheric and Oceanic Technology","topic":"Ocean Waves and Remote Sensing","field":"Earth and Planetary Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"U.S. Army Corps of Engineers; Danish Hydrocarbon Research and Technology Centre, Technical University of Denmark; California Department of Parks and Recreation","keywords":"Computer science; Wind wave; Geology; Data mining; Remote sensing; Machine learning; Oceanography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00114033,0.001200447,0.0006577747,0.001897,0.0005529349,0.0007876217,0.002356912,0.001179691,0.009035009],"category_scores_gemma":[0.005466951,0.0003982577,0.001207648,0.00208506,0.0003255339,0.001169462,0.00178369,0.001552296,0.009135382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005112433,"about_ca_system_score_gemma":0.001289787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01394051,"about_ca_topic_score_gemma":0.02367126,"domain_scores_codex":[0.9992478,0.0000952917,0.0001296677,0.0001680805,0.0002699376,0.00008913509],"domain_scores_gemma":[0.9983588,0.0004444359,0.0001181143,0.0005407895,0.0004031962,0.0001347334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004023945,0.0002422182,0.008630668,0.0008573755,0.0001559473,0.0002414603,0.0001017839,0.01169544,0.00330571,0.0020729,0.9266786,0.04561552],"study_design_scores_gemma":[0.001567149,0.0004282602,0.04668618,0.0004006381,0.0001286474,0.0005292381,0.0004553841,0.145207,0.01477343,0.01075577,0.7787772,0.0002911156],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0151427,0.0002337085,0.01042092,0.0004297318,0.0002804018,0.0002956168,0.9529564,0.0175816,0.002658885],"genre_scores_gemma":[0.009637585,0.00007382299,0.01536326,0.00008743502,0.00002306058,0.0003464464,0.9731747,0.0004504411,0.0008432519],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01394051,"threshold_uncertainty_score":0.03022516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02454425741288255,"score_gpt":0.2220590951717692,"score_spread":0.1975148377588866,"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."}}