{"id":"W4393475002","doi":"10.5281/zenodo.10256598","title":"Mountie Hat (Toon)","year":2018,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Engineering and Material Science Research","field":"Materials Science","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":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001722567,0.0002649213,0.000270618,0.0003264653,0.00225491,0.002430175,0.002917797,0.0002021546,0.08119536],"category_scores_gemma":[0.0009085049,0.000253459,0.00006614975,0.0005054798,0.0004596161,0.0003297303,0.002489613,0.0003680517,0.07692114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002448128,"about_ca_system_score_gemma":0.00001191122,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00012841,"about_ca_topic_score_gemma":0.000001072741,"domain_scores_codex":[0.9969415,0.0003274725,0.0003174063,0.000727708,0.0008907865,0.0007951066],"domain_scores_gemma":[0.9979635,0.00002609102,0.0001337619,0.0009847566,0.0005730301,0.0003188707],"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":[0.00002470897,0.00005874992,1.257063e-8,0.0001494591,0.000009084747,0.00001649346,0.00004693521,0.0000124115,0.02541179,0.00008910157,0.9721127,0.002068606],"study_design_scores_gemma":[0.0001755044,0.0002294245,0.000005441444,0.00007138507,0.00001288441,0.0000751723,0.00002227744,0.00002655993,0.003501998,0.00005998105,0.9955305,0.0002888684],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008355316,0.00006425643,0.000353696,0.0002101064,0.0009295238,0.0003931462,0.9890504,0.0008418615,0.00732148],"genre_scores_gemma":[0.0006950171,0.0002341291,0.0002316651,0.00007765574,0.0008576596,1.074107e-7,0.9960063,0.0009811033,0.0009163475],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02341785,"threshold_uncertainty_score":0.9999918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0295566670812096,"score_gpt":0.2595505951725968,"score_spread":0.2299939280913872,"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."}}