{"id":"W2517679670","doi":"10.1371/journal.pone.0158901","title":"The Economic Value of the Greater Montreal Blue Network (Quebec, Canada): A Contingent Choice Study Using Real Projects to Estimate Non-Market Aquatic Ecosystem Services Benefits","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais; Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Centre Hospitalier Universitaire de Sherbrooke; Université de Sherbrooke","funders":"David Suzuki Foundation","keywords":"Recreation; Unit (ring theory); Ecosystem services; Biodiversity; Aquatic ecosystem; Ecosystem; Carbon sequestration; Total economic value; Willingness to pay; Value (mathematics); Environmental resource management; Freshwater ecosystem; Natural resource economics; Business; Environmental science; Ecology; Economics; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002685249,0.0004939272,0.000301139,0.001110537,0.001153641,0.00141621,0.001192306,0.0007052389,0.003310863],"category_scores_gemma":[0.01003686,0.0002842189,0.0003862863,0.001996424,0.001383802,0.0008386708,0.0005964382,0.0007244604,0.0001304719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03028037,"about_ca_system_score_gemma":0.007636094,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9371638,"about_ca_topic_score_gemma":0.9529088,"domain_scores_codex":[0.9988406,0.0006584813,0.00002467355,0.0001266831,0.0001675647,0.000182101],"domain_scores_gemma":[0.991771,0.005233398,0.0009832103,0.0003455802,0.001011141,0.0006557471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001491363,0.001462488,0.7914949,0.0001634549,0.0005099449,0.0008819663,0.001718496,0.1530508,0.00139957,0.01780026,0.003913538,0.02611338],"study_design_scores_gemma":[0.0002712652,0.0006128539,0.6384064,0.00008452492,0.0001363601,0.0001150017,0.002975155,0.3491673,0.0007977069,0.002264756,0.005035169,0.0001335184],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9944746,0.0001096368,0.001651698,0.0001672149,0.000003459599,0.0001526738,0.0008898502,0.000007764183,0.002542991],"genre_scores_gemma":[0.996287,0.00007257409,0.001864519,0.00003237339,0.000002540604,0.00008791982,0.0004505828,0.000003516866,0.001198907],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06283623,"threshold_uncertainty_score":0.2197005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05068428251145676,"score_gpt":0.2038221302150703,"score_spread":0.1531378477036135,"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."}}