{"id":"W4405912060","doi":"10.1016/j.oceaneng.2024.120050","title":"HADAD: Hexagonal A-Star with Differential Algorithm Designed for weather routing","year":2024,"lang":"en","type":"article","venue":"Ocean Engineering","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Agencia Estatal de Investigación; European Regional Development Fund; Banco Bilbao Vizcaya Argentaria; Fundación BBVA; Ministerio de Ciencia e Innovación; Mitacs; European Commission","keywords":"Star (game theory); Hexagonal crystal system; Differential (mechanical device); Routing (electronic design automation); Computer science; Algorithm; Meteorology; Environmental science; Physics; Engineering; Aerospace engineering; Computer network; Astrophysics; Chemistry; Crystallography","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":[0.00006426025,0.0001113369,0.00007634292,0.00002519883,0.00007128516,0.00006698362,0.00007367088,0.00003126306,0.0000884843],"category_scores_gemma":[0.000005159683,0.00009235218,0.00003510153,0.0001231094,0.00002231687,0.00006580857,0.0000235588,0.00007663586,0.00004250732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006891332,"about_ca_system_score_gemma":0.000006436044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002290217,"about_ca_topic_score_gemma":0.000002088602,"domain_scores_codex":[0.9993643,0.000003861659,0.00008663857,0.0002190023,0.0001178224,0.0002083992],"domain_scores_gemma":[0.9997677,0.00004559276,0.00001042062,0.0001152931,0.000003171956,0.0000577843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003308709,0.0001211863,0.0004078686,0.0001509009,0.0002202241,0.00004726977,0.002538091,0.1318802,0.364421,0.003086457,0.006857657,0.4902361],"study_design_scores_gemma":[0.0001522006,0.00004777953,0.001095872,0.0000522415,0.00002877681,0.00002316981,0.00003213344,0.9564727,0.01079475,0.000053047,0.03102567,0.0002216502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1647922,0.00002349332,0.8340032,0.00008656803,0.00009575693,0.0001591695,0.000008736975,0.0002164121,0.0006144585],"genre_scores_gemma":[0.8989269,0.000001313282,0.09995423,0.00001305063,0.0001388251,0.000002848534,0.00001131106,0.00004046108,0.0009111302],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8245925,"threshold_uncertainty_score":0.3766012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005523755648146013,"score_gpt":0.1925475865710798,"score_spread":0.1870238309229338,"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."}}