{"id":"W6967200374","doi":"10.48668/vt8ump/c7v1mk","title":"sanderia.PacBio.fastq.gz.MD5","year":2023,"lang":"en","type":"dataset","venue":"CUHK Research Data Repository","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Queen's University","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","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","metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["open_science","research_integrity"],"category_scores_codex":[0.01333915,0.001198545,0.001433298,0.002850609,0.001839472,0.002220361,0.01754075,0.001612483,0.0006923719],"category_scores_gemma":[0.008523528,0.001192211,0.0002838598,0.003537777,0.002224158,0.001602782,0.0221122,0.007018099,0.3859072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001483756,"about_ca_system_score_gemma":0.004006418,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01505163,"about_ca_topic_score_gemma":0.002455011,"domain_scores_codex":[0.9785215,0.004187671,0.001592453,0.004648775,0.007561231,0.003488376],"domain_scores_gemma":[0.9704008,0.002486828,0.0005984927,0.02384725,0.001262038,0.001404661],"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":[0.0002752379,0.0004093969,0.00001733576,0.0009777956,0.0005732444,0.005109586,0.00002273079,0.000001569007,0.002532301,0.00000824399,0.9898258,0.0002467794],"study_design_scores_gemma":[0.0007725515,0.0002175023,0.0001864345,0.000790621,0.0001818398,0.000312206,0.0002184911,0.00005938102,0.0004495377,0.00005324641,0.9956361,0.00112207],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004275456,0.001475592,0.000002592746,0.0001346726,0.004379965,0.00186435,0.9888552,0.0008918435,0.002353076],"genre_scores_gemma":[0.000009441971,0.001514709,0.00008781964,0.00004131307,0.005894573,0.0004233153,0.9720966,0.0006534981,0.01927878],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3852148,"threshold_uncertainty_score":0.9998281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5571518294041781,"score_gpt":0.5380763801755616,"score_spread":0.01907544922861648,"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."}}