{"id":"W4386055512","doi":"10.1139/cgj-2023-0168","title":"A data driven real-time perception method of rock condition in TBM construction","year":2023,"lang":"en","type":"article","venue":"Canadian Geotechnical Journal","topic":"Tunneling and Rock Mechanics","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; People's Government of Jilin Province; China Railway","keywords":"Rock mass classification; Identification (biology); Data mining; Computer science; Index (typography); Statistics; Geotechnical engineering; Mining engineering; Engineering; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004932595,0.0000895725,0.0001691854,0.0004616561,0.00007665491,0.00001947677,0.0002506834,0.0001871254,0.0001628912],"category_scores_gemma":[0.000095132,0.00009561193,0.00003986047,0.0004070188,0.00001088266,0.0001345387,0.00003196935,0.000427537,0.00008276302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002520743,"about_ca_system_score_gemma":0.000153819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002043744,"about_ca_topic_score_gemma":0.00267544,"domain_scores_codex":[0.9990925,0.00005505873,0.0003116977,0.0001338553,0.0001317602,0.0002751467],"domain_scores_gemma":[0.9993668,0.00004419377,0.00004557079,0.0002476334,0.00004359092,0.0002521817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00000555817,0.000005875442,0.00004312553,0.00002937867,0.00002505928,0.00009128232,0.0001121408,0.9253766,0.03944857,0.0001940727,0.01059462,0.0240737],"study_design_scores_gemma":[0.0002122454,0.00002168646,0.001463959,0.00009556653,0.00001610274,0.0004231281,0.0001660803,0.9942392,0.0001283822,0.0009757965,0.002142,0.000115918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4928653,0.00008869599,0.5007353,0.001345873,0.001770695,0.0004416021,0.00104839,0.0009163041,0.0007878383],"genre_scores_gemma":[0.9909395,0.0004196973,0.008146042,0.00002229321,0.0001855248,0.000003015015,0.0002038353,0.00003077372,0.00004933462],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4980742,"threshold_uncertainty_score":0.3898941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02026300310183818,"score_gpt":0.2649871922689308,"score_spread":0.2447241891670926,"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."}}