{"id":"W6902158996","doi":"10.6084/m9.figshare.25621419.v1","title":"Supplementary File 2 - Sample summary profile.pdf","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Skin Protection and Aging","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sample (material); Public health; Public access; Data collection; Large sample","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00002311669,0.00008666261,0.00009012924,0.00007774222,0.0000528608,0.00004403531,0.0000468517,0.00004082811,0.9907865],"category_scores_gemma":[0.0002943821,0.00007453796,0.00007290361,0.0001770732,0.000002897497,0.00005979515,0.00005203486,0.0001835713,0.01443052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004926638,"about_ca_system_score_gemma":0.00007854134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004830316,"about_ca_topic_score_gemma":0.000008358103,"domain_scores_codex":[0.9993826,0.00001056799,0.0001073958,0.0001933232,0.0001418276,0.0001642698],"domain_scores_gemma":[0.9996125,0.0001337476,0.00001256414,0.000136542,0.00002536438,0.00007924398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007114594,0.00001305229,0.00004074336,0.0003935205,0.00002260018,0.0001126578,0.00004416516,1.725996e-7,0.0001220525,0.000004615443,0.9895743,0.009664998],"study_design_scores_gemma":[0.0001688771,0.00004808237,0.000666698,0.003047634,0.0000127007,0.00006871226,0.00005752851,0.0005016619,0.003049097,0.00003442173,0.9922594,0.00008514839],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001082802,0.0004122102,0.000004453707,0.001156491,0.0001720587,0.0004638547,0.9755327,0.0002553331,0.02189464],"genre_scores_gemma":[0.006411342,0.000003017539,0.0007765545,0.00147654,0.0006186357,0.0005564106,0.9701746,0.00003082801,0.01995206],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.976356,"threshold_uncertainty_score":0.9863369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03459689834187742,"score_gpt":0.2951460648646153,"score_spread":0.2605491665227379,"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."}}