{"id":"W4393526938","doi":"10.5281/zenodo.10306283","title":"Penny (Coin)","year":2018,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"National Identity and Symbolism","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001689158,0.0001582351,0.0001864389,0.0003513642,0.006753394,0.001882996,0.002138718,0.0002463765,0.0950788],"category_scores_gemma":[0.002325912,0.0001843576,0.00008610741,0.0006131558,0.0006222328,0.0003551631,0.001075738,0.0004316783,0.05846131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000284277,"about_ca_system_score_gemma":0.00002370891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001009189,"about_ca_topic_score_gemma":0.00007213632,"domain_scores_codex":[0.9971166,0.0007685678,0.0002580932,0.0004402086,0.0009773613,0.0004391871],"domain_scores_gemma":[0.9980006,0.00004392603,0.0001712809,0.0004796345,0.001059491,0.0002450811],"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":[0.00001081067,0.00007395018,8.587416e-8,0.00003068993,0.00002805858,0.00000977921,0.000636791,3.972127e-7,0.000007366954,0.005414192,0.9913916,0.002396267],"study_design_scores_gemma":[0.0001572643,0.00005957222,0.00003218845,0.00002925,0.00002315461,0.00001094485,0.0002569225,0.000001737723,0.000002876466,0.0009775539,0.998244,0.0002045509],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006376175,0.00006055477,0.0000356094,0.0008920908,0.0005344366,0.0003605927,0.8841661,0.00038363,0.1135033],"genre_scores_gemma":[0.0003249006,0.0005731994,0.00003636698,0.0002501539,0.001648829,2.709004e-8,0.9913923,0.0005649931,0.005209275],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.108294,"threshold_uncertainty_score":0.9991531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05456318949035611,"score_gpt":0.3105265428445644,"score_spread":0.2559633533542083,"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."}}