{"id":"W4398916051","doi":"10.7910/dvn/v1rjpf/uowfsx","title":"cbb20150816_03.txt.gz","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Computer science","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004919253,0.001051074,0.001069489,0.0004606293,0.0002064587,0.0003260852,0.00262497,0.0007414455,0.6631066],"category_scores_gemma":[0.001145744,0.00111568,0.0003575415,0.0006905645,0.0003014992,0.0006881516,0.002051756,0.001527817,0.9997336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003686367,"about_ca_system_score_gemma":0.0005464193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005401553,"about_ca_topic_score_gemma":0.0003519478,"domain_scores_codex":[0.9950104,0.0003158492,0.0007997918,0.001566186,0.001305973,0.001001824],"domain_scores_gemma":[0.9944762,0.0001385304,0.0006419327,0.003762793,0.0001637518,0.0008167653],"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":[0.0001869357,0.0001625381,0.000002282987,0.0002687283,0.0003005539,0.001239847,0.00002207662,0.00000369866,0.00009923203,0.0000410497,0.9975952,0.00007787372],"study_design_scores_gemma":[0.001050704,0.00009606896,0.00001174034,0.0001408443,0.000649558,0.00007212542,0.0000547644,0.00001980185,0.00003998144,0.00002712341,0.9966652,0.001172022],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000001858902,1.036966e-7,0.00001106187,0.000002360032,0.001440338,0.0007009282,0.9965338,0.0005254179,0.0007841649],"genre_scores_gemma":[0.000001429964,0.0002278753,0.0003926529,0.001376155,0.001368063,0.00007985505,0.9957965,0.0002697511,0.0004877028],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.336627,"threshold_uncertainty_score":0.9991294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02633682481075176,"score_gpt":0.2574856251301236,"score_spread":0.2311488003193719,"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."}}