{"id":"W373158566","doi":"","title":"汽水域調査のためのローコスト・コンパクトな音響調査機器(サイドスキャンソーナー)のシステム化","year":2004,"lang":"ja","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003519906,0.0008639754,0.000688707,0.0003512601,0.001278093,0.0002448781,0.0009504785,0.0007700348,0.0002435976],"category_scores_gemma":[0.0004215442,0.0009358315,0.0002938452,0.0008558528,0.001405394,0.002014253,0.0003914832,0.001432186,0.0008426723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008909316,"about_ca_system_score_gemma":0.001028984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001343052,"about_ca_topic_score_gemma":0.0004158439,"domain_scores_codex":[0.9958217,0.00006533333,0.001099727,0.001052798,0.0009005513,0.001059878],"domain_scores_gemma":[0.9974449,0.0001518777,0.0001607144,0.001601169,0.0002797445,0.0003616386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001661921,0.0003555673,0.0007257306,0.000585767,0.0005182829,0.002414907,0.0006058014,0.02720585,0.01033975,0.9526498,0.003938755,0.0004936515],"study_design_scores_gemma":[0.01062773,0.001301641,0.01208496,0.005992773,0.001327554,0.008123336,0.004194982,0.00272772,0.1149317,0.1137453,0.7170988,0.007843507],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4800521,0.05059975,0.03756564,0.004065842,0.04027145,0.001971762,0.007126554,0.005506006,0.3728409],"genre_scores_gemma":[0.9864399,0.001445512,0.007499703,0.0001599106,0.002251086,0.00009767193,0.001312553,0.00007811594,0.0007155076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8389045,"threshold_uncertainty_score":0.9999353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0125447450810886,"score_gpt":0.2292644835709213,"score_spread":0.2167197384898327,"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."}}