{"id":"W2517061221","doi":"10.21083/partnership.v11i1.3661","title":"What Do Health Libraries Tweet About? A Content Analysis","year":2016,"lang":"en","type":"article","venue":"Partnership The Canadian Journal of Library and Information Practice and Research","topic":"Web and Library Services","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"University of Toronto","keywords":"Library science; Medical library; Content analysis; Political science; Sociology; Computer science; Social science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.00343315,0.0003608201,0.000469828,0.01173407,0.002482588,0.004214603,0.0005996641,0.0007107076,0.003548899],"category_scores_gemma":[0.0170235,0.0002643858,0.0004668679,0.01315487,0.001512815,0.004383061,0.002745134,0.0008710556,0.001267616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003628335,"about_ca_system_score_gemma":0.00207982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009075748,"about_ca_topic_score_gemma":0.009654287,"domain_scores_codex":[0.9968885,0.001354816,0.0003167621,0.0003387224,0.0006700784,0.0004311729],"domain_scores_gemma":[0.9821917,0.0128035,0.001278511,0.0004120261,0.002925989,0.0003882158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0005135491,0.0002340503,0.1246552,0.002658745,0.00009476647,0.001347159,0.6376809,0.0005403039,0.008188464,0.008153398,0.02908906,0.1868444],"study_design_scores_gemma":[0.00003049954,0.0001737304,0.1530059,0.001340938,0.0001089994,0.0005749773,0.6813977,0.004291889,0.005732556,0.003370802,0.1498235,0.0001484599],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9467636,0.0008178703,0.008441018,0.004618636,0.0001929358,0.001789576,0.01551674,0.0002394312,0.02162016],"genre_scores_gemma":[0.9430641,0.001983731,0.023438,0.001964856,0.0003225646,0.00344736,0.01179914,0.0003085009,0.01367191],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01173407,"threshold_uncertainty_score":0.02632546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09178970398247448,"score_gpt":0.3334987980372316,"score_spread":0.2417090940547572,"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."}}