{"id":"W2111272836","doi":"10.1109/tdc.2006.1668721","title":"Project Evaluation and Selection at BC Hydro","year":2006,"lang":"en","type":"article","venue":"","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Hydro (Canada)","funders":"","keywords":"Reliability (semiconductor); Index (typography); Customer satisfaction; Selection (genetic algorithm); Duration (music); Computer science; Reliability engineering; Process (computing); Operations research; Engineering; Business; Marketing; Artificial intelligence; Power (physics)","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":[0.0001915635,0.00004701006,0.00004853548,0.00002522548,0.00002724533,0.0000104429,0.00001511644,0.00003162959,0.00003960014],"category_scores_gemma":[0.000009740407,0.00004079736,0.00001088993,0.0000688311,0.000007353294,0.00006537129,0.000006083366,0.0000250127,0.0000251781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001100655,"about_ca_system_score_gemma":0.000006895837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003031701,"about_ca_topic_score_gemma":0.0005763451,"domain_scores_codex":[0.9996576,0.00001414138,0.00008016656,0.00008027688,0.00008187977,0.00008597785],"domain_scores_gemma":[0.9999053,0.00001031645,0.000007014432,0.00004179823,0.00002613863,0.000009357735],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007667269,0.0001727594,0.05221612,0.001417051,0.000130732,0.000004274304,0.001254678,0.2124049,0.2615905,0.01402582,0.4119664,0.04474006],"study_design_scores_gemma":[0.000392112,0.00003186177,0.01698843,0.00002174721,0.00001783958,0.00002483965,0.00002106878,0.9015114,0.01786268,0.0008426033,0.06211038,0.0001750194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8640372,0.0002686263,0.008982495,0.00003707375,0.0001874112,0.0003753556,9.557336e-7,0.0003270923,0.1257838],"genre_scores_gemma":[0.9976754,0.000007470423,0.0002282466,0.00000615323,0.00003953946,0.0000293048,0.00000294448,0.000005720438,0.00200527],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6891066,"threshold_uncertainty_score":0.1663668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008890356361735564,"score_gpt":0.2242965596275264,"score_spread":0.2154062032657908,"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."}}