{"id":"W1929460918","doi":"10.1186/s13104-015-1570-5","title":"Mail merge can be used to create personalized questionnaires in complex surveys","year":2015,"lang":"en","type":"article","venue":"BMC Research Notes","topic":"Survey Methodology and Nonresponse","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; University of Ottawa; Western University","funders":"Canadian Institutes of Health Research; Ottawa Hospital Research Institute","keywords":"Personalization; Comprehension; Computer science; Merge (version control); Informed consent; The Internet; Medical education; Data science; Medicine; World Wide Web; Information retrieval; Alternative medicine","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2075671,0.0001183321,0.0002728787,0.0004536075,0.000491195,0.00009310321,0.0004978126,0.0001631641,0.0005549814],"category_scores_gemma":[0.2406155,0.0001122351,0.00005706216,0.00135429,0.0009360129,0.0001259486,0.0001399617,0.0003384918,0.0001564911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002835694,"about_ca_system_score_gemma":0.001606988,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1680573,"about_ca_topic_score_gemma":0.5663864,"domain_scores_codex":[0.8755457,0.1219393,0.0002215169,0.0003649693,0.001129711,0.0007988039],"domain_scores_gemma":[0.957131,0.04146709,0.00003276417,0.000272043,0.0005490798,0.0005480641],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003486821,0.0001484979,0.9183939,0.00001333558,0.00001772276,0.00005089555,0.05812442,0.00003821394,0.001739558,0.005932975,0.01051431,0.00153935],"study_design_scores_gemma":[0.0008090044,0.0001364328,0.9652771,0.00002712016,0.000002402072,8.461375e-7,0.007387391,0.00004292528,0.0005304166,0.00282365,0.02278189,0.0001808627],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9835274,0.000166141,0.001001015,0.01206473,0.0002043008,0.0004887822,0.00003571913,0.00006968038,0.002442297],"genre_scores_gemma":[0.9918917,0.00002706526,0.004077336,0.0001472607,0.0001814254,0.00008524123,0.00002109675,0.00001602717,0.003552869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3983291,"threshold_uncertainty_score":0.8374826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8720271096295334,"score_gpt":0.6140061248055335,"score_spread":0.2580209848239999,"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."}}