{"id":"W6929576696","doi":"10.5064/f6buax58/nnji8o","title":"Burke_EDI_NENA.QC004.ResearcherSurvey.2017.09.21.rtf","year":2018,"lang":"en","type":"dataset","venue":"Syracuse University Qualitative Data Repository","topic":"Mathematical Biology Tumor Growth","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Identifier; Survey data collection; Plan (archaeology); Survey methodology; Identification (biology); Scale (ratio); Data collection","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","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006654025,0.001014036,0.001604243,0.0006841191,0.0008578397,0.000154542,0.006474321,0.001191693,0.0007347144],"category_scores_gemma":[0.01052826,0.0009720436,0.000318948,0.0006621234,0.002550328,0.0008269,0.004873745,0.002043144,0.001451282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006816425,"about_ca_system_score_gemma":0.0007840344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001148566,"about_ca_topic_score_gemma":0.0004290098,"domain_scores_codex":[0.9872812,0.006898401,0.001039005,0.002197467,0.001467157,0.001116743],"domain_scores_gemma":[0.9796518,0.01099089,0.001258199,0.006595025,0.0008781787,0.0006258811],"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":[0.0002629893,0.000580851,0.000004607662,0.001114413,0.0008930401,0.001158978,0.002390233,2.324769e-8,0.00005530354,0.003854904,0.9896716,0.00001306693],"study_design_scores_gemma":[0.0009321741,0.0003236409,0.00001351653,0.0004469381,0.0006412663,0.00009646435,0.007114504,0.0000202912,0.00008179592,0.007699536,0.9814894,0.001140494],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006828697,0.00009421782,0.00038276,0.0002286536,0.001154441,0.0008931967,0.9921124,0.0002578181,0.004193649],"genre_scores_gemma":[0.00004026484,0.0001220737,0.006562792,0.00006841221,0.0009691105,0.000006016344,0.9835228,0.00008043701,0.008628135],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.008589635,"threshold_uncertainty_score":0.9993262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2642391340010815,"score_gpt":0.4404236988846091,"score_spread":0.1761845648835276,"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."}}