{"id":"W2802940346","doi":"10.7939/r34953","title":"Assessment of Pipeline Installation Using the Eliminator: a New Guided Boring Machine","year":2015,"lang":"en","type":"article","venue":"University of Alberta Library","topic":"Non-Destructive Testing Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pipeline (software); Computer science; Engineering; Operating system","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":[0.002339239,0.0008061769,0.0006488003,0.002753241,0.0005362547,0.001131418,0.000999207,0.0007488414,0.001133502],"category_scores_gemma":[0.003652994,0.0004315044,0.000471889,0.001653045,0.0005248804,0.001123056,0.0004806769,0.0004426944,0.000333018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001566435,"about_ca_system_score_gemma":0.002107714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01704362,"about_ca_topic_score_gemma":0.04969046,"domain_scores_codex":[0.9971598,0.0002455445,0.00009946219,0.0001851162,0.002204666,0.0001052875],"domain_scores_gemma":[0.9971609,0.001026624,0.0006709938,0.0001057291,0.0009482096,0.00008749119],"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":[0.001419499,0.0004000145,0.2205971,0.002685669,0.000163245,0.002168925,0.002039512,0.07069556,0.226963,0.002195714,0.002663157,0.4680087],"study_design_scores_gemma":[0.00009389117,0.006826808,0.5974647,0.0004694746,0.0005638835,0.001740154,0.003391691,0.1610367,0.2090081,0.001030204,0.01811431,0.0002599873],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9243982,0.00141882,0.0642642,0.0001789323,0.00002915496,0.0003694892,0.0007028038,0.000471125,0.00816725],"genre_scores_gemma":[0.9514186,0.001598104,0.04283263,0.00002337393,0.000008664444,0.00007280883,0.0003657497,0.00004132227,0.003638766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01704362,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02896385236776594,"score_gpt":0.2406882287557811,"score_spread":0.2117243763880152,"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."}}