{"id":"W2370928996","doi":"","title":"GEDAP: A Comprehensive Experimental Acquisition and Analysis Package for Hydraulic Model Test","year":2000,"lang":"en","type":"article","venue":"Journal of Oceanograpgy of Huanghai &bohai Seas","topic":"Advanced Computational Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Flexibility (engineering); Reliability (semiconductor); Computer science; Data acquisition; Test (biology); Software; Reliability engineering; Function (biology); Software package; Simulation; Engineering; Geology; Mathematics; Operating system; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002086694,0.001300331,0.001157051,0.001457468,0.0005911932,0.0008661044,0.00256265,0.0006343397,0.05524944],"category_scores_gemma":[0.005558413,0.0007474546,0.0006690074,0.00150458,0.0005040456,0.001749072,0.001553929,0.002159796,0.01117572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004090139,"about_ca_system_score_gemma":0.001814638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004351504,"about_ca_topic_score_gemma":0.004962622,"domain_scores_codex":[0.9988814,0.0001578487,0.0001079296,0.0001308139,0.0006302845,0.00009176481],"domain_scores_gemma":[0.9971883,0.001034968,0.000156807,0.0005088422,0.0009970958,0.0001140661],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000873775,0.0004083467,0.006165137,0.00171174,0.0002803893,0.000530367,0.0004497538,0.06001382,0.05200184,0.01951195,0.5695606,0.2884923],"study_design_scores_gemma":[0.0007104233,0.0005320152,0.01146267,0.0001745352,0.0001723187,0.000612048,0.0001654535,0.4921501,0.09381662,0.01705493,0.3826862,0.000462691],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007443763,0.00008462992,0.7667716,0.0001882585,0.0002182513,0.000756498,0.038991,0.1770579,0.008488107],"genre_scores_gemma":[0.0941392,0.0003813903,0.7535347,0.0003979129,0.0001092591,0.00563796,0.07747945,0.05242109,0.01589907],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05524944,"threshold_uncertainty_score":0.1848278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01878447251388063,"score_gpt":0.2973313023904708,"score_spread":0.2785468298765902,"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."}}