{"id":"W2092307878","doi":"10.1002/rob.20427","title":"Field repair and construction of large hydropower equipment with a portable robot","year":2011,"lang":"en","type":"article","venue":"Journal of Field Robotics","topic":"Power Line Inspection Robots","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec","funders":"Hydro-Québec","keywords":"Penstock; Robot; Hydropower; Engineering; Work (physics); Field (mathematics); Task (project management); Schedule; Automation; Computer science; Mechanical engineering; Electrical engineering; Systems engineering; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001283275,0.00009588579,0.0002128471,0.000106136,0.0000234741,0.000007012403,0.00006679635,0.00008490503,0.0001805586],"category_scores_gemma":[0.00003369863,0.0000788167,0.00006233974,0.00009062994,0.00002109301,0.0001479334,0.00001823678,0.0002451924,0.000001067387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001978483,"about_ca_system_score_gemma":0.00002577418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001253884,"about_ca_topic_score_gemma":0.00001776585,"domain_scores_codex":[0.9992576,0.000009411347,0.0003808581,0.00006220693,0.0001491931,0.0001406839],"domain_scores_gemma":[0.9994882,0.00004451429,0.0001607499,0.0001256867,0.0001066437,0.00007423273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002219589,0.001864156,0.3785162,0.001825839,0.004594248,0.001875221,0.009803188,0.4654701,0.01272799,0.04168833,0.06817544,0.01123968],"study_design_scores_gemma":[0.01733012,0.02787981,0.05145145,0.003856386,0.002346012,0.01592647,0.007225356,0.1598377,0.6751032,0.01293293,0.0222225,0.003888116],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.246023,0.001009688,0.727799,0.0007053849,0.002502151,0.0001870601,0.000002819442,0.0001554709,0.02161551],"genre_scores_gemma":[0.9004368,0.0002015132,0.09905776,0.0001016431,0.00009766558,4.691656e-7,2.300235e-7,0.00001439486,0.00008959032],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6623752,"threshold_uncertainty_score":0.3214052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009732916409385449,"score_gpt":0.215058291893908,"score_spread":0.2053253754845226,"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."}}