{"id":"W6902085246","doi":"10.6073/pasta/0f574bf189dfc1b3a3a6d37368094e54","title":"Coastal SEES Collaborative Research: Non-Market Value Meta-Data on Willingness to Pay for Coastal Marsh Habitat Change","year":2020,"lang":"en","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Marsh; Habitat; Valuation (finance); Wetland; Wildlife; Metadata; Willingness to pay; Guild","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02770017,0.001367937,0.0047552,0.01351991,0.000728896,0.004550181,0.003197964,0.002477073,0.02666416],"category_scores_gemma":[0.2225147,0.001091273,0.0144882,0.01857252,0.0007764917,0.002448105,0.004915047,0.002619076,0.003579614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002403042,"about_ca_system_score_gemma":0.008236787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01521133,"about_ca_topic_score_gemma":0.03429217,"domain_scores_codex":[0.9678311,0.01581214,0.007422904,0.003234768,0.005025784,0.000673378],"domain_scores_gemma":[0.8164386,0.1323884,0.01810108,0.01812279,0.01339686,0.001552223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002531643,0.0001094088,0.02654884,0.4925935,0.2513742,0.0003206025,0.001574331,0.003551843,0.001093653,0.009292232,0.1297317,0.08127802],"study_design_scores_gemma":[0.004401383,0.0006592979,0.06202031,0.2128039,0.2832974,0.0005438388,0.0009178178,0.001385809,0.001493462,0.01778511,0.4142879,0.0004037693],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01024909,0.1059303,0.01439124,0.003355708,0.0006021691,0.00288466,0.8532288,0.001249458,0.008108505],"genre_scores_gemma":[0.2308861,0.07267261,0.0848645,0.005337326,0.0005032262,0.04105604,0.5562441,0.001664549,0.006771527],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02770017,"threshold_uncertainty_score":0.1464943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3665783312891557,"score_gpt":0.4517694803711867,"score_spread":0.08519114908203101,"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."}}