{"id":"W2247034589","doi":"10.22004/ag.econ.306697","title":"The Keystone XL Pipeline Project","year":2011,"lang":"en","type":"article","venue":"AgEcon Search (University of Minnesota, USA)","topic":"Diverse Research and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pipeline (software); Keystone species; Computer science; Biology; Ecology; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006570405,0.00009125401,0.0001256092,0.0001532508,0.000561199,0.00004854615,0.001926876,0.00004592647,0.0002296002],"category_scores_gemma":[0.00003064792,0.0000824086,0.00009193557,0.0006272616,0.0003940323,0.0005499174,0.0007002059,0.0001846777,0.0006804239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003627305,"about_ca_system_score_gemma":0.0002140562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002156521,"about_ca_topic_score_gemma":0.0005540882,"domain_scores_codex":[0.9986515,0.0001213201,0.00009880021,0.0003039407,0.0004156125,0.0004088159],"domain_scores_gemma":[0.9986827,0.0001589132,0.00006275668,0.0007033551,0.0002402238,0.0001520179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001599112,0.0007478305,0.002387251,0.00007858354,0.0001833617,0.0003218676,0.01716806,0.000006843571,0.003362862,0.3718856,0.1215383,0.4821596],"study_design_scores_gemma":[0.003741717,0.001124468,0.07998042,0.0000885528,0.00005882889,0.00007780259,0.02258371,0.04424093,0.01110566,0.005986813,0.829888,0.001123102],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4642022,0.0003664761,0.2725067,0.009224277,0.0002397429,0.001673685,0.00007653553,0.000270163,0.2514403],"genre_scores_gemma":[0.9451644,0.0009391119,0.02364016,0.00006032921,0.00004083143,0.000002783056,0.000007427001,0.00001017945,0.03013478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7083497,"threshold_uncertainty_score":0.87457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07739642669991409,"score_gpt":0.26468613370338,"score_spread":0.1872897070034659,"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."}}