{"id":"W2296075867","doi":"10.14288/1.0095721","title":"Monitoring of Northern mega-projects : missed opportunities? : a case study of the Norman Weils ollfield development and pipeline project","year":2010,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Arctic and Russian Policy Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mega-; Pipeline (software); Environmental planning; Engineering; Geography","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":[0.006279396,0.0003072983,0.0003414327,0.0008969308,0.007704945,0.002508451,0.001450567,0.001709403,0.001874619],"category_scores_gemma":[0.009426248,0.0005064696,0.000193577,0.001840417,0.0026081,0.002331968,0.002695911,0.001458049,0.0001658359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005626043,"about_ca_system_score_gemma":0.005302944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03086648,"about_ca_topic_score_gemma":0.102057,"domain_scores_codex":[0.9946643,0.003448727,0.0001290649,0.0003058842,0.0008473379,0.0006047116],"domain_scores_gemma":[0.9937739,0.003506803,0.001375764,0.0002966229,0.0004446769,0.0006020913],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002368901,0.001018712,0.0753921,0.0006503531,0.00003731824,0.05847776,0.7486808,0.002613042,0.003446613,0.01292104,0.004727967,0.0917973],"study_design_scores_gemma":[0.00001450373,0.0005091452,0.04285877,0.0002655024,0.0000145487,0.006321654,0.9086586,0.001380675,0.001569677,0.001055128,0.03731378,0.0000380019],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911635,0.0001970363,0.0009486473,0.00149394,0.000007389498,0.000101731,0.00002461783,0.000007579836,0.006055524],"genre_scores_gemma":[0.9940985,0.0005920076,0.001661766,0.0001753429,0.000008984146,0.0001075301,0.00002096676,0.000007458369,0.003327345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03086648,"threshold_uncertainty_score":0.06137365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0535370049918692,"score_gpt":0.2548218583627913,"score_spread":0.2012848533709221,"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."}}