{"id":"W4224001476","doi":"10.1186/s42238-022-00132-1","title":"Analyzing sentiments and themes on cannabis in Canada using 2018 to 2020 Twitter data","year":2022,"lang":"en","type":"article","venue":"Journal of Cannabis Research","topic":"Cannabis and Cannabinoid Research","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Canadian Institutes of Health Research","keywords":"Cannabis; Thematic analysis; Legalization; Social media; Sentiment analysis; Government (linguistics); Advertising; Content analysis; Internet privacy; Psychology; Political science; Business; Computer science; Sociology; Law; Psychiatry; Qualitative research; Social science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00389105,0.0001983695,0.0005461899,0.001284922,0.0003735951,0.0001004905,0.0008185905,0.00004516162,0.0008290904],"category_scores_gemma":[0.0006508218,0.0001704587,0.00007532538,0.001802071,0.0001066599,0.0001622013,0.001395487,0.001851887,0.000003949483],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.004792112,"about_ca_system_score_gemma":0.01094057,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5368732,"about_ca_topic_score_gemma":0.2086706,"domain_scores_codex":[0.9940388,0.0005669413,0.000716711,0.0004966868,0.003247507,0.000933386],"domain_scores_gemma":[0.9975573,0.00002946329,0.0001630713,0.0007967187,0.0006643711,0.0007890476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008748622,0.0001387919,0.02143475,0.00007872152,0.00010178,0.001943676,0.0004967604,0.0007327835,0.005656069,0.000003868918,0.9615854,0.006952539],"study_design_scores_gemma":[0.002288664,0.001505325,0.07270988,0.0002229014,0.00004602969,0.0009323235,0.007593378,0.003416226,0.001103908,0.0000467799,0.9098391,0.000295505],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8994874,0.001460865,0.000006829473,0.09783546,0.0002470586,0.0005018329,0.00009925783,0.000002978476,0.0003583546],"genre_scores_gemma":[0.9831169,0.0001851225,0.0001831469,0.001479619,0.0004770859,0.00003513959,0.00001957385,0.00006436816,0.01443902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3282026,"threshold_uncertainty_score":0.9990283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1014396733591238,"score_gpt":0.4073338042681194,"score_spread":0.3058941309089957,"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."}}