{"id":"W7055117741","doi":"","title":"Canadian newspaper coverage on harm reduction featuring bereaved mothers: A mixed methods analysis","year":2023,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Laser Design and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Newspaper; Harm; Harm reduction; Reduction (mathematics); Content analysis","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":[0.0145221,0.0008026899,0.00149225,0.00721973,0.00473884,0.003333737,0.002765347,0.001596477,0.01044872],"category_scores_gemma":[0.07078879,0.0008037707,0.001694283,0.01705849,0.000994405,0.00120032,0.002122318,0.001667904,0.00065758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02396167,"about_ca_system_score_gemma":0.05803251,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9141595,"about_ca_topic_score_gemma":0.9595933,"domain_scores_codex":[0.9814817,0.005125524,0.001759736,0.00133636,0.008526787,0.001770022],"domain_scores_gemma":[0.9351417,0.02986619,0.009750237,0.001700512,0.02182454,0.001716842],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.003167921,0.002705565,0.6851923,0.01450986,0.005483354,0.0005817561,0.0464752,0.0003605481,0.0007011686,0.0018653,0.05773221,0.1812248],"study_design_scores_gemma":[0.000611107,0.0007169947,0.9082739,0.006681854,0.006210249,0.000202738,0.0400116,0.0009096834,0.0005928176,0.0004052943,0.03512728,0.0002564354],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8940632,0.02003568,0.003061839,0.004745192,0.0005681225,0.008612532,0.04932887,0.0001112804,0.01947338],"genre_scores_gemma":[0.9318556,0.01239037,0.01262938,0.007192078,0.0003406905,0.01292485,0.01178745,0.0001365339,0.01074314],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08584052,"threshold_uncertainty_score":0.1738548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1769169855390581,"score_gpt":0.5139275121285851,"score_spread":0.337010526589527,"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."}}