{"id":"W1986754214","doi":"10.1061/(asce)0733-9364(2007)133:10(743)","title":"Modeling the Effect of Subjective Factors on Productivity of Trenchless Technology Application to Buried Infrastructure Systems","year":2007,"lang":"en","type":"article","venue":"Journal of Construction Engineering and Management","topic":"Geotechnical Engineering and Underground Structures","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Trenchless technology; Productivity; Schedule; Analytic hierarchy process; Production (economics); Engineering; Software; Fuzzy logic; Installation; Operations research; Computer science; Industrial engineering; Reliability engineering; Artificial intelligence; Pipeline transport; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002373552,0.0007359091,0.0003479653,0.000623208,0.0002613019,0.001000168,0.0004671169,0.0004594675,0.0008813983],"category_scores_gemma":[0.01200556,0.0003385727,0.0005296842,0.0006702212,0.0004073715,0.0007985819,0.0006696772,0.0003948115,0.00009403106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001243946,"about_ca_system_score_gemma":0.000804015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01102715,"about_ca_topic_score_gemma":0.008168397,"domain_scores_codex":[0.9989194,0.0005782993,0.00005329429,0.0001149687,0.0002070774,0.0001269474],"domain_scores_gemma":[0.9892146,0.008206571,0.001211492,0.0002668592,0.0008996259,0.0002007781],"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":[0.0002211885,0.0001376789,0.03450453,0.00007001734,0.00005716622,0.0001612365,0.0002851314,0.9448509,0.002524518,0.001422691,0.0000926671,0.01567226],"study_design_scores_gemma":[0.000007743925,0.0001457853,0.009259922,0.000004348529,0.00002067624,0.00001502589,0.00007795985,0.9889924,0.0009126333,0.0004679099,0.00008563137,0.000009972467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9061191,0.00007483774,0.09179098,0.00005011696,0.000007492896,0.00007379569,0.00007281384,0.0000533707,0.001757605],"genre_scores_gemma":[0.9939334,0.00003853429,0.005679297,0.000002618573,0.000002074332,0.00002554979,0.00003110108,0.0000046436,0.0002827502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01102715,"threshold_uncertainty_score":0.02192593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002238740969505923,"score_gpt":0.1860182105646232,"score_spread":0.1837794695951173,"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."}}