{"id":"W2547132872","doi":"10.1142/s2382624x16500326","title":"Valuing a Logging Externality: Loss of the Water Purification Service of Temperate Coastal Rainforests","year":2016,"lang":"en","type":"article","venue":"Water Economics and Policy","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Mitacs","keywords":"Logging; Environmental science; Ecosystem services; Turbidity; Externality; Watershed; Sedimentation; Business; Environmental resource management; Natural resource economics; Ecosystem; Ecology; Economics; Computer science; Forestry; Sediment; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.001677211,0.0003802458,0.0003386534,0.0005189268,0.0004180133,0.002255159,0.0007279325,0.001183328,0.001223105],"category_scores_gemma":[0.005019654,0.0003003339,0.0005998902,0.0006891112,0.001575787,0.00192885,0.001494148,0.001179219,0.0000505907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00318451,"about_ca_system_score_gemma":0.0008673212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01748365,"about_ca_topic_score_gemma":0.02890088,"domain_scores_codex":[0.9994116,0.0002219678,0.00003366575,0.00008644154,0.00009312483,0.0001531169],"domain_scores_gemma":[0.9965532,0.001796804,0.001106112,0.0001472401,0.0001302704,0.0002663236],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006536827,0.0005958348,0.5111343,0.00008617485,0.0002545711,0.001741432,0.0006686549,0.4421805,0.005854033,0.02091012,0.0004909889,0.01542962],"study_design_scores_gemma":[0.00004400211,0.0005997116,0.3624313,0.00005408849,0.0001344608,0.0003247594,0.00266022,0.6086167,0.001955752,0.02210335,0.0009841706,0.00009150717],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959434,0.00003984782,0.002123814,0.0002150566,0.00000244563,0.00001200992,0.0000503529,0.000005368579,0.001607657],"genre_scores_gemma":[0.9992842,0.00003323906,0.0003459756,0.00001950142,0.000002722728,0.000003750538,0.00002719048,0.00000199258,0.000281368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01748365,"threshold_uncertainty_score":0.03476375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04551774959994418,"score_gpt":0.2148574133197913,"score_spread":0.1693396637198472,"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."}}