{"id":"W6917423668","doi":"10.57745/4l78zf","title":"DataGrowthRecords.tab","year":2024,"lang":"en","type":"dataset","venue":"Recherche Data Gouv France","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nautical Research Society","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":["metaepi_narrow","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.009293932,0.001551986,0.001547361,0.0006471603,0.0001726534,0.0007232455,0.01515033,0.003179402,0.002823689],"category_scores_gemma":[0.007075366,0.001527816,0.0002229628,0.003016458,0.0004123846,0.001593627,0.007646167,0.009893185,0.5802891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001002185,"about_ca_system_score_gemma":0.001497547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002594077,"about_ca_topic_score_gemma":0.002444694,"domain_scores_codex":[0.9896581,0.001876915,0.001283732,0.004235149,0.00146099,0.001485144],"domain_scores_gemma":[0.9770548,0.001890766,0.0005936492,0.01982605,0.0001877878,0.000446909],"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":[0.00004924188,0.0002053678,0.000006225431,0.001530467,0.0004166913,0.0003148822,0.00001807872,0.000001002547,0.00006356557,0.00001032265,0.9908566,0.006527493],"study_design_scores_gemma":[0.0004027293,0.00004389922,0.00001506458,0.001119991,0.0007540892,0.00009482863,0.00002024428,0.000239369,0.00004145884,0.0007288044,0.9948701,0.001669372],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000002678265,0.01745511,0.00008426351,0.0003286937,0.0047012,0.0009269682,0.9748481,0.0008753898,0.0007775949],"genre_scores_gemma":[2.124787e-7,0.008235651,0.006635742,0.0005746,0.004181146,0.0001599849,0.9758888,0.0005627109,0.003761086],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5774655,"threshold_uncertainty_score":0.9997228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4144744875582169,"score_gpt":0.4579242623627684,"score_spread":0.04344977480455148,"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."}}