{"id":"W3111615218","doi":"10.1111/ipd.12769","title":"Transparency in clinical trials: Adding value to paediatric dental research","year":2020,"lang":"en","type":"article","venue":"International Journal of Paediatric Dentistry","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Ministério da Saúde; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Transparency (behavior); Medicine; Clinical trial; Consolidated Standards of Reporting Trials; MEDLINE; Research design; Paediatric dentistry; Sample size determination; Impact factor; Clinical study design; Clinical research; Reliability (semiconductor); Family medicine; Dentistry; Power (physics); Statistics","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":["metaresearch","scholarly_communication","insufficient_payload"],"consensus_categories":["metaresearch","insufficient_payload"],"category_scores_codex":[0.3460476,0.0002362238,0.003211959,0.001960511,0.00006423707,0.001133061,0.005088859,0.0001664717,0.00423637],"category_scores_gemma":[0.2949603,0.0001406169,0.003359783,0.003524916,0.00005061426,0.0004737842,0.0003164642,0.00102662,0.002680437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001365276,"about_ca_system_score_gemma":0.0003664994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009639629,"about_ca_topic_score_gemma":0.00001570367,"domain_scores_codex":[0.893726,0.04471182,0.03754001,0.001214807,0.0222514,0.000555978],"domain_scores_gemma":[0.9554374,0.02886283,0.0094597,0.0008985808,0.004419085,0.0009224637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002121407,0.0002915915,0.7310376,0.00002662582,0.0005213722,0.00160118,0.0006166677,0.001157605,0.0001079825,0.0007816851,0.1465984,0.1170471],"study_design_scores_gemma":[0.007424766,0.001109731,0.6627623,0.000296523,0.001135633,0.001241892,0.006632115,0.01075736,0.0001036414,0.009082196,0.2984368,0.001017008],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9398487,0.003956899,0.03694985,0.006268454,0.009464171,0.0006944386,0.0001128013,0.000005410242,0.002699244],"genre_scores_gemma":[0.988974,0.0003141452,0.004538084,0.0005276538,0.005185563,0.000007845293,0.000004686999,0.00001419739,0.0004337736],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1518384,"threshold_uncertainty_score":0.9999039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8978591830817043,"score_gpt":0.6777640374414955,"score_spread":0.2200951456402088,"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."}}