{"id":"W2045967462","doi":"10.1115/ipc2014-33359","title":"Achieving Efficiency in Environmental Assessment Through Focused Selection of Valued Components","year":2014,"lang":"en","type":"article","venue":"","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Stantec (Canada)","funders":"","keywords":"Scope (computer science); Government (linguistics); Environmental impact assessment; Baseline (sea); Process (computing); Environmental planning; Business; Environmental resource management; Political science; Computer science; Environmental science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.04502349,0.001127758,0.001074542,0.007294037,0.002868309,0.01345386,0.003567331,0.001824424,0.006422979],"category_scores_gemma":[0.05281564,0.0009440873,0.001230873,0.005215537,0.004026299,0.008731931,0.01446849,0.002541624,0.003185077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009360001,"about_ca_system_score_gemma":0.02513596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00949041,"about_ca_topic_score_gemma":0.01870549,"domain_scores_codex":[0.9542073,0.01922868,0.002909316,0.003419186,0.01856649,0.001669095],"domain_scores_gemma":[0.9629436,0.01172617,0.002091252,0.006018687,0.01591732,0.001302995],"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":[0.0002341527,0.0002807226,0.01022744,0.001915082,0.0001472278,0.0005230905,0.01443545,0.005658614,0.01333853,0.243608,0.02029498,0.6893367],"study_design_scores_gemma":[0.0001937556,0.0004997488,0.01574254,0.006637034,0.0004133552,0.0008918184,0.01944328,0.01417884,0.0233322,0.4173428,0.5010453,0.0002793213],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06207662,0.002739278,0.6718043,0.007992844,0.0002367337,0.003834387,0.0008025868,0.0008851201,0.249628],"genre_scores_gemma":[0.2917865,0.00239603,0.6758363,0.001971107,0.00006648211,0.002739833,0.001444672,0.0007032717,0.02305586],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04502349,"threshold_uncertainty_score":0.2381098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01431100802307246,"score_gpt":0.2704560276286738,"score_spread":0.2561450196056013,"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."}}