{"id":"W331567734","doi":"10.21236/ada417137","title":"Using a Laser Underwater Camera Image Enhancer for Mine Warfare Applications: What is Gained?","year":2002,"lang":"en","type":"report","venue":"","topic":"Image Enhancement Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Underwater; Laser; Enhancer; Image (mathematics); Computer science; Computer vision; Computer graphics (images); Artificial intelligence; Engineering; Geology; Optics; Physics; Oceanography; Chemistry","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":[0.001798117,0.0007554138,0.0005869382,0.0005501576,0.0002988193,0.001268081,0.0008154216,0.001360289,0.003459506],"category_scores_gemma":[0.00154188,0.0001643344,0.0003184883,0.0004390916,0.0005745846,0.002489998,0.0004751305,0.0004772148,0.00116188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003325593,"about_ca_system_score_gemma":0.0005114302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002640173,"about_ca_topic_score_gemma":0.006558652,"domain_scores_codex":[0.9994519,0.0001526638,0.00002821385,0.00006379762,0.0002229737,0.00008039311],"domain_scores_gemma":[0.998917,0.0003043523,0.000102091,0.00008835525,0.0005109698,0.00007724803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009700574,0.001498293,0.02306503,0.002530067,0.0001924989,0.0009090868,0.000471209,0.002010491,0.1639878,0.001842828,0.004530544,0.7979921],"study_design_scores_gemma":[0.0005308193,0.02731718,0.07003585,0.00115494,0.001647658,0.01453282,0.003464481,0.03382077,0.7369216,0.002014813,0.1081099,0.0004491738],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7093546,0.05166099,0.1726462,0.01038097,0.0004484353,0.0009484526,0.0004672114,0.002175695,0.0519175],"genre_scores_gemma":[0.7646136,0.04332247,0.1664119,0.002023162,0.0004162648,0.0001879987,0.001075852,0.0001542371,0.02179452],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003459506,"threshold_uncertainty_score":0.0115732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06997831454547994,"score_gpt":0.3504884706568975,"score_spread":0.2805101561114176,"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."}}