{"id":"W4234193524","doi":"10.3410/f.726857072.793524461","title":"Faculty Opinions recommendation of Notes from the field: Lessons learned from using ecosystem service approaches to inform real-world decisions.","year":2016,"lang":"en","type":"dataset","venue":"Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature","topic":"Web and Library Services","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Field (mathematics); Service (business); Environmental resource management; Data science; Knowledge management; Computer science; Medical education; Geography; Business; Environmental science; Marketing; Medicine; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005401192,0.001341867,0.001017038,0.005158439,0.001204321,0.004434801,0.003656819,0.002430475,0.04308473],"category_scores_gemma":[0.03931772,0.0005400852,0.001020575,0.008833588,0.000614691,0.003852131,0.002644923,0.002405789,0.06916783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003047454,"about_ca_system_score_gemma":0.004446861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06408222,"about_ca_topic_score_gemma":0.1990181,"domain_scores_codex":[0.9964994,0.0009213989,0.0004767102,0.0006681976,0.001136597,0.0002976558],"domain_scores_gemma":[0.9815208,0.005577825,0.001388278,0.005289978,0.004880728,0.00134244],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003682663,0.00001576312,0.002409401,0.0001551978,0.00001321468,0.00001429329,0.00002403012,0.0001648003,0.00002971209,0.0005822745,0.9915343,0.005020279],"study_design_scores_gemma":[0.0001269356,0.00001266219,0.00816503,0.0005259193,0.00002181961,0.00004841169,0.000370461,0.001978649,0.0002999743,0.00384727,0.9845649,0.00003803242],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00128373,0.0003765908,0.0007429613,0.002727892,0.0004522702,0.00005631424,0.9838337,0.0007084378,0.009817991],"genre_scores_gemma":[0.004031217,0.0002765176,0.002091496,0.0003931172,0.00009238616,0.0001028805,0.9872242,0.000149193,0.005638931],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9945988,"threshold_uncertainty_score":0.1441327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1969688912975932,"score_gpt":0.3772611059463529,"score_spread":0.1802922146487597,"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."}}