{"id":"W1985543183","doi":"10.1115/ipc2002-27295","title":"High-Speed Tandem GMAW for Pipeline Welding","year":2002,"lang":"en","type":"article","venue":"4th International Pipeline Conference, Parts A and B","topic":"Welding Techniques and Residual Stresses","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"TransCanada (Canada)","funders":"","keywords":"Gas metal arc welding; Welding; Welding power supply; Mechanical engineering; Pipeline (software); Torch; Electrogas welding; Robot welding; Laser beam welding; Materials science; Arc welding; Engineering; Filler metal","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00009484526,0.0001818061,0.0001983083,0.0001040756,0.00008160933,0.0001237186,0.0001846202,0.00009598624,0.0007842919],"category_scores_gemma":[0.00005825175,0.0001560419,0.00005620281,0.00006077192,0.00004410328,0.0001204196,0.00004487789,0.0001240661,0.00001710632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002265463,"about_ca_system_score_gemma":0.000005703026,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002888293,"about_ca_topic_score_gemma":0.00002240032,"domain_scores_codex":[0.999095,0.000007537607,0.0002953997,0.0002105641,0.0001684368,0.0002230708],"domain_scores_gemma":[0.9995304,0.00007192941,0.00004744627,0.0001102094,0.000153184,0.0000867809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000650602,0.0002353133,0.002524646,0.0002188722,0.0002127594,0.00003732023,0.0004636695,0.0125987,0.003795202,0.05182071,0.8386039,0.08942385],"study_design_scores_gemma":[0.001013193,0.00007184178,0.0002853934,0.0001678391,0.00003359707,0.0000212741,0.00004639774,0.4223305,0.0144374,0.005051857,0.5561081,0.0004326093],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3175312,0.003925457,0.5128146,0.01473137,0.00750255,0.001799058,0.0007272281,0.00327472,0.1376938],"genre_scores_gemma":[0.9902462,0.0009745505,0.002682179,0.0001351588,0.0007266468,0.0000269016,0.00006244113,0.0000248741,0.005121089],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6727149,"threshold_uncertainty_score":0.8587447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03564447315540734,"score_gpt":0.25523804544227,"score_spread":0.2195935722868627,"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."}}