{"id":"W7062762264","doi":"","title":"US Wind Development Pipeline Grew by 6,146 MW in First Quarter","year":2019,"lang":"en","type":"other","venue":"","topic":"Adaptive optics and wavefront sensing","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Pipeline (software); Quarter (Canadian coin); Wind power; Pipeline transport","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00005407952,0.0003150467,0.0003652436,0.0001060955,0.0000321614,0.0000365349,0.0001150923,0.0001211046,0.004519156],"category_scores_gemma":[6.309414e-7,0.0002753014,0.00006395169,0.00006079381,0.00002214265,0.00002715894,0.00005595372,0.0001909932,0.001302206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004037916,"about_ca_system_score_gemma":0.00006797494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001212881,"about_ca_topic_score_gemma":0.0003887902,"domain_scores_codex":[0.9989133,0.00001275656,0.0002613364,0.0003585422,0.00014571,0.0003083939],"domain_scores_gemma":[0.9995241,0.00001790839,0.0001355273,0.0002407866,0.00001851186,0.00006315647],"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":[0.000004094934,0.00009606175,0.00425192,0.00001822828,0.00006720841,0.000002286238,0.0001053382,0.00001031558,0.00001245568,0.001055656,0.9908674,0.003508984],"study_design_scores_gemma":[0.0005013481,0.0000121141,0.0002274681,0.0001682624,0.00001040954,1.684487e-7,0.0001063685,0.0002864104,0.00007597058,0.00004388547,0.9981654,0.0004021632],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0004502626,0.0001312578,0.009670445,0.000113768,0.0002541188,0.0003182087,0.00003835864,0.00002870311,0.9889949],"genre_scores_gemma":[0.02958304,0.000004165048,0.003162055,0.00009472646,0.0003583798,0.000003067071,0.0002388207,0.0002371679,0.9663185],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02913278,"threshold_uncertainty_score":0.9999699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007635109516194055,"score_gpt":0.2104307724182922,"score_spread":0.2027956629020981,"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."}}