{"id":"W4399097131","doi":"10.1186/s12954-024-01017-7","title":"Implementing Canada’s first national virtual phone based overdose prevention service: lessons learned from creating the National Overdose Response Service (NORS)","year":2024,"lang":"en","type":"article","venue":"Harm Reduction Journal","topic":"Opioid Use Disorder Treatment","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Canadian Institutes of Health Research; Health Canada","keywords":"Harm reduction; Hotline; Service (business); Opioid overdose; Phone; Public relations; Public health; Business; Health psychology; Internet privacy; Medicine; Nursing; Marketing; Political science; Engineering; (+)-Naloxone; Opioid","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":[0.008335676,0.0004598824,0.0002935138,0.0008598603,0.0148213,0.007111634,0.00292964,0.002537332,0.003860082],"category_scores_gemma":[0.01286509,0.000376542,0.0005940792,0.001073903,0.006053934,0.003443256,0.00453158,0.007353995,0.0004538387],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06177761,"about_ca_system_score_gemma":0.3694975,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9473057,"about_ca_topic_score_gemma":0.9843528,"domain_scores_codex":[0.992238,0.002009682,0.0001561705,0.0002933101,0.002753934,0.002549057],"domain_scores_gemma":[0.9835358,0.001747312,0.0003415528,0.0003387751,0.00519928,0.0088373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001818822,0.001096828,0.03985691,0.001546308,0.0000594358,0.003686738,0.06084875,0.001638552,0.002288065,0.03607121,0.2846783,0.5680471],"study_design_scores_gemma":[0.000107907,0.0007873867,0.06773238,0.003479709,0.0000886703,0.001035927,0.144696,0.001906331,0.002188377,0.005537681,0.772206,0.0002336804],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1418843,0.009788293,0.007670484,0.7537129,0.004393878,0.001268378,0.0005793523,0.0005176439,0.08018477],"genre_scores_gemma":[0.7771361,0.02489757,0.05460697,0.1020329,0.001043741,0.0005475905,0.000916405,0.0003705737,0.03844812],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9382224,"threshold_uncertainty_score":0.44823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05470997782914718,"score_gpt":0.3484947491908561,"score_spread":0.2937847713617089,"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."}}