{"id":"W2129255159","doi":"10.3152/147154603781766527","title":"Lessons from practice: towards successful follow-up","year":2003,"lang":"en","type":"article","venue":"Impact Assessment and Project Appraisal","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Transportation of Ontario; Environment and Climate Change Canada","funders":"","keywords":"Stakeholder; Environmental planning; Political science; Stakeholder engagement; Relation (database); Environmental impact assessment; Environmental resource management; Public relations; Business; Process management; Engineering ethics; Computer science; Engineering; Geography; Environmental science","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006655539,0.0004522166,0.0004071182,0.00006063631,0.0003993156,0.0003080986,0.0002751222,0.0001956289,0.00364518],"category_scores_gemma":[0.000214258,0.000369466,0.0001802806,0.0003525233,0.0002779324,0.001451204,0.0002447384,0.0004101525,0.0001439481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004543556,"about_ca_system_score_gemma":0.0001943308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006388735,"about_ca_topic_score_gemma":0.0002008187,"domain_scores_codex":[0.9970793,0.0004251453,0.0003638929,0.0006158967,0.0008015239,0.0007142259],"domain_scores_gemma":[0.9986572,0.0004043576,0.0002270609,0.0003705477,0.00001161767,0.0003292629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002056973,0.0009399161,0.9271193,0.0000132027,0.0004127995,0.00006296707,0.004375834,0.00003425253,0.009333198,0.001812947,0.01278552,0.04290433],"study_design_scores_gemma":[0.004074974,0.0008168779,0.8891641,0.00002984863,0.0002932274,0.00005915095,0.006190615,0.0002679471,0.00171192,0.002063215,0.09408832,0.001239833],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8726039,0.000102729,0.0006664704,0.0007982574,0.000693795,0.0004970134,0.00008561347,0.00008904919,0.1244632],"genre_scores_gemma":[0.9926987,0.000217173,0.005796397,0.0003521151,0.0001141438,0.00006384156,0.00007944342,0.00004861728,0.0006295126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1238337,"threshold_uncertainty_score":0.9998757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03245550484531987,"score_gpt":0.4242833686957416,"score_spread":0.3918278638504217,"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."}}