{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007424607,0.0001549672,0.0007106674,0.000487987,0.00006180127,0.00001254057,0.00008930496,0.0001886852,0.0004043135],"category_scores_gemma":[0.00005616309,0.00009670176,0.0001395127,0.0007608863,0.0008563374,0.0002720364,0.00001839231,0.0001419472,0.000006210768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006438955,"about_ca_system_score_gemma":0.0001726501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005308509,"about_ca_topic_score_gemma":0.00003111134,"domain_scores_codex":[0.9984291,0.00006738439,0.0005580017,0.0001910405,0.0005619334,0.000192554],"domain_scores_gemma":[0.9981677,0.0001301342,0.0002893644,0.0003460121,0.0008427312,0.0002240589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001139546,0.0006422782,0.05816628,0.002640198,0.008128935,0.000009387345,0.03850373,0.0008592539,0.3396537,0.4295402,0.006422856,0.1142937],"study_design_scores_gemma":[0.01928462,0.0111403,0.2645505,0.00104001,0.007142865,0.0000226509,0.01743569,0.3054397,0.1568397,0.0005582417,0.2156525,0.0008931909],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9305494,0.001113679,0.03922936,0.02599352,0.000590929,0.001399725,0.0001117152,0.00005057855,0.0009610678],"genre_scores_gemma":[0.9956447,0.0000852426,0.0005180557,0.001298738,0.0002694363,0.0000285326,0.0008845467,0.000010097,0.001260685],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.428982,"threshold_uncertainty_score":0.442695,"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."}}