{"id":"W3001869323","doi":"10.2217/rme-2019-0092","title":"Contact Us for More Information: An Analysis of Public Enquiries about Stem Cells","year":2019,"lang":"en","type":"article","venue":"Regenerative Medicine","topic":"Biomedical Ethics and Regulation","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Stem cell; Data science; Computational biology; Biology; Cell biology; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.01183239,0.0001905634,0.0002685563,0.004333853,0.001514867,0.002597174,0.0004987068,0.0007954498,0.03373834],"category_scores_gemma":[0.07425441,0.0002160367,0.0002142934,0.00485255,0.0009971932,0.003158054,0.003137631,0.0009428329,0.007135617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002048387,"about_ca_system_score_gemma":0.004925842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006440125,"about_ca_topic_score_gemma":0.00676997,"domain_scores_codex":[0.9891889,0.006677505,0.001008114,0.0004725961,0.002125969,0.0005269034],"domain_scores_gemma":[0.8771092,0.08871501,0.0145826,0.003454562,0.01252646,0.003612159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.000469739,0.0004145543,0.223696,0.004185148,0.00006138848,0.001413362,0.2520491,0.0003044626,0.002163782,0.006187167,0.2280174,0.281038],"study_design_scores_gemma":[0.00005987491,0.0002080125,0.1359792,0.002871094,0.00004811654,0.0007230794,0.3607917,0.0005874377,0.001291354,0.001777097,0.495568,0.00009485299],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7881331,0.003908546,0.006578331,0.02979196,0.0004310034,0.002832102,0.05722516,0.0008063749,0.1102934],"genre_scores_gemma":[0.9293289,0.00351445,0.00727203,0.006950083,0.0001845454,0.003517361,0.01095904,0.0005025437,0.037771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03373834,"threshold_uncertainty_score":0.112866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04666712643311768,"score_gpt":0.33232072414569,"score_spread":0.2856535977125724,"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."}}