{"id":"W4393454403","doi":"10.5281/zenodo.10342992","title":"Mile 0 Sign - Object Capture","year":2021,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sign (mathematics); Object (grammar); Mile; Computer science; Geography; Cartography; Artificial intelligence; Geodesy; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005958771,0.004830274,0.001664747,0.003566835,0.0009938561,0.002933179,0.004556393,0.002779134,0.05412523],"category_scores_gemma":[0.003413827,0.001059324,0.002491047,0.005186947,0.0005844401,0.002965099,0.002930483,0.0030725,0.1071565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002568746,"about_ca_system_score_gemma":0.002264381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06980956,"about_ca_topic_score_gemma":0.1358051,"domain_scores_codex":[0.9988726,0.0001093639,0.0001097256,0.0004438235,0.0002768947,0.000187721],"domain_scores_gemma":[0.9991344,0.0001427706,0.00005973532,0.0003558117,0.0002268518,0.00008036388],"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":[0.00009029092,0.00004518592,0.0009140862,0.0005885501,0.00003416467,0.00005740641,0.00003448583,0.0009391058,0.0003363514,0.0008908075,0.988833,0.007236553],"study_design_scores_gemma":[0.0001335995,0.00002742052,0.00336072,0.0002715007,0.00003354589,0.0001778749,0.0001292668,0.00530491,0.00162814,0.002453297,0.9864137,0.00006615416],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006439885,0.0002400096,0.001010172,0.0001088587,0.00007979749,0.00006110274,0.9858782,0.009550451,0.00242739],"genre_scores_gemma":[0.0009903712,0.00007879555,0.001321892,0.00005037267,0.000004599241,0.00009520452,0.9961966,0.0003327956,0.0009294002],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06980956,"threshold_uncertainty_score":0.1810669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02222393011007517,"score_gpt":0.256226605803431,"score_spread":0.2340026756933559,"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."}}