{"id":"W4398260233","doi":"10.7910/dvn/ii5jzg/etg9a6","title":"MSP_F_100_NFL_4_39.xlsx","year":2020,"lang":"tl","type":"dataset","venue":"Harvard Dataverse","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Context (archaeology); Resolution (logic); Computer science; History; Artificial intelligence; Archaeology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00197146,0.002488998,0.001809447,0.005421695,0.001439048,0.004352229,0.004047432,0.002921622,0.5062839],"category_scores_gemma":[0.01687467,0.001204489,0.001495481,0.008352591,0.0008472202,0.002748141,0.003398104,0.002133037,0.417919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001485987,"about_ca_system_score_gemma":0.002861087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01502642,"about_ca_topic_score_gemma":0.02037242,"domain_scores_codex":[0.9982413,0.0002848002,0.0002397887,0.0004503864,0.0003729957,0.0004107342],"domain_scores_gemma":[0.9920471,0.003149615,0.0006704029,0.001540845,0.001968513,0.000623574],"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":[0.00003823418,0.00001345582,0.0003594966,0.0005478664,0.00001440426,0.000008596724,0.00002140434,0.00006380229,0.00005072554,0.0002913446,0.9975578,0.001032872],"study_design_scores_gemma":[0.0005501386,0.00002884424,0.003108067,0.0005604044,0.00002867606,0.00004375025,0.0001305435,0.0001783416,0.0003584341,0.001803979,0.9931645,0.00004435136],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004209016,0.0000165953,0.00003655253,0.00005096286,0.00001700705,0.000008438721,0.9989538,0.0003562489,0.0005182567],"genre_scores_gemma":[0.0004911691,0.0000433029,0.0003512635,0.0001072377,0.00001989499,0.0002001153,0.996778,0.0004654542,0.00154362],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4937161,"threshold_uncertainty_score":0.704226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02899132947345974,"score_gpt":0.2755982653031389,"score_spread":0.2466069358296792,"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."}}