{"id":"W1987717197","doi":"10.1016/j.apor.2015.01.016","title":"A tool for ROV-based seabed friction measurement","year":2015,"lang":"en","type":"article","venue":"Applied Ocean Research","topic":"Geotechnical Engineering and Underground Structures","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Division of Arctic Sciences; Australian Research Council; Western University; Shell","keywords":"Seabed; Remotely operated underwater vehicle; Marine engineering; Remotely operated vehicle; Engineering; Actuator; Consistency (knowledge bases); Interface (matter); Geotechnical engineering; Structural engineering; Geology; Computer science; Robot; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0003683457,0.0007264132,0.0008663925,0.001704619,0.0003440206,0.0008571661,0.0009992417,0.0008818397,0.007432575],"category_scores_gemma":[0.00132722,0.0003972353,0.0003232309,0.001152141,0.0001571943,0.000802667,0.00135383,0.0003859837,0.003787213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001725648,"about_ca_system_score_gemma":0.0004085666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001524026,"about_ca_topic_score_gemma":0.00206016,"domain_scores_codex":[0.9994643,0.0000493042,0.00002583147,0.00008711348,0.0003274518,0.00004598462],"domain_scores_gemma":[0.999506,0.0001003283,0.00004072449,0.0001225299,0.0001909029,0.00003949246],"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":[0.0004499209,0.000197195,0.009523346,0.0004142275,0.0001593455,0.0003841392,0.0003368428,0.01101796,0.2478065,0.002560449,0.01969034,0.7074597],"study_design_scores_gemma":[0.0001794741,0.0005743915,0.03376088,0.0001978233,0.0001818498,0.001456366,0.0003285061,0.6214644,0.2236043,0.002750697,0.1152567,0.0002445946],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04356957,0.0003713938,0.9190881,0.00009631848,0.0002027409,0.0001707475,0.002578355,0.02766704,0.006255719],"genre_scores_gemma":[0.5984237,0.0003577713,0.3824083,0.0002561318,0.00009008709,0.0004098451,0.004949431,0.001352573,0.01175214],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007432575,"threshold_uncertainty_score":0.02486444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09146345891178705,"score_gpt":0.2952461157454996,"score_spread":0.2037826568337126,"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."}}