{"id":"W1898527705","doi":"10.25043/19098642.94","title":"Underwater Multi-influence Measurements as a Mean to Characterize the Overall Vessel Signature and Protect the Marine Environment","year":2014,"lang":"en","type":"article","venue":"Ciencia y tecnología de buques","topic":"Underwater Acoustics Research","field":"Earth and Planetary Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Submarine Engineering (Canada)","funders":"","keywords":"Underwater; Signature (topology); Environmental science; Marine engineering; Modular design; Computer science; Acoustics; Engineering; Geology; Oceanography; Physics","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":[0.0003776158,0.0006202074,0.0004384679,0.001325535,0.0003108105,0.0005356108,0.0004613571,0.0005312418,0.001370967],"category_scores_gemma":[0.0009725087,0.0001984239,0.0002235259,0.001009994,0.0002810975,0.001084428,0.001138357,0.0004804863,0.0007141114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000176658,"about_ca_system_score_gemma":0.0002234609,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000937349,"about_ca_topic_score_gemma":0.002407913,"domain_scores_codex":[0.9991733,0.0001642049,0.00002675756,0.0001365359,0.0004453113,0.00005367636],"domain_scores_gemma":[0.9996432,0.00006717727,0.00006511995,0.0000662292,0.0001254706,0.00003287111],"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":[0.0002865001,0.00009800104,0.03851566,0.0004653072,0.000127111,0.0003424516,0.0005915797,0.008917045,0.6747081,0.001663907,0.001905995,0.2723784],"study_design_scores_gemma":[0.00004545111,0.001029673,0.2959395,0.0002465673,0.0004025715,0.002291714,0.001349265,0.1497469,0.4861836,0.004554447,0.05796366,0.0002466471],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4485401,0.003442318,0.5142793,0.0004859087,0.0003531839,0.0001548955,0.001055087,0.001895323,0.02979389],"genre_scores_gemma":[0.8934869,0.001153354,0.1010801,0.0001429929,0.0001354166,0.00006105679,0.0004687539,0.00018905,0.003282462],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001370967,"threshold_uncertainty_score":0.004586339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02951407796151775,"score_gpt":0.2365632205180733,"score_spread":0.2070491425565555,"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."}}