{"id":"W6917336947","doi":"10.57745/4ngrwr","title":"RNAseq data on DROPS Dent panel","year":2025,"lang":"en","type":"dataset","venue":"Recherche Data Gouv France","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Raw data; Pattern recognition (psychology); Data set; Data visualization","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":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.001265705,0.0005265959,0.0004957713,0.00006648291,0.0001376585,0.00006994777,0.005998824,0.001014903,0.00003279003],"category_scores_gemma":[0.001537322,0.0005064142,0.00007504452,0.0001900649,0.0001254474,0.000002458691,0.005857415,0.0008614903,0.00005851369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004872891,"about_ca_system_score_gemma":0.0004760011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004300358,"about_ca_topic_score_gemma":0.0004213683,"domain_scores_codex":[0.9966313,0.000371125,0.0004291716,0.001848721,0.0002624283,0.0004572678],"domain_scores_gemma":[0.9891083,0.0001941602,0.0002232424,0.0102765,0.00009108501,0.0001066932],"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":[0.00005004849,0.000124319,0.0000288763,0.0001551844,0.0003112804,0.000008534818,0.000004266051,0.00000796885,0.002871692,0.000003075574,0.9913681,0.00506671],"study_design_scores_gemma":[0.0003560576,0.0001130071,0.0001494897,0.0001236103,0.0001512041,0.000005142414,0.00001552774,0.00003164096,0.001322284,0.00003919585,0.9971811,0.0005117815],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005254635,0.01054658,0.0001341117,0.0002830174,0.0009053261,0.0003536431,0.9869577,0.000006769737,0.0002874278],"genre_scores_gemma":[0.00006240763,0.03325971,0.001666815,0.001358171,0.0008820094,0.00003395477,0.9605067,0.00002753959,0.002202669],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02645094,"threshold_uncertainty_score":0.9997388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2565836310937078,"score_gpt":0.3918028428337408,"score_spread":0.135219211740033,"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."}}