{"id":"W6950322321","doi":"10.5281/zenodo.8173345","title":"OREONI - Data acquisition for OHBM2023","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Geophysics and Gravity Measurements","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Data acquisition; Data collection; Knowledge acquisition; Identification (biology); Automation","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001230639,0.001744923,0.00148109,0.001833357,0.000997359,0.002682482,0.002294043,0.001470951,0.4501145],"category_scores_gemma":[0.002772591,0.0008384411,0.0009415146,0.001938247,0.0003491943,0.002254761,0.003452652,0.001598923,0.4030569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008524091,"about_ca_system_score_gemma":0.001462684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01411305,"about_ca_topic_score_gemma":0.01858216,"domain_scores_codex":[0.9992378,0.0000470758,0.00003932584,0.0001712458,0.0003417453,0.0001628365],"domain_scores_gemma":[0.9986534,0.000100942,0.00005067274,0.0004633779,0.0005616565,0.0001698162],"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":[0.0002362183,0.00002272447,0.0004181537,0.000170899,0.00002072179,0.00002885943,0.00003884498,0.0001502459,0.001589642,0.0005236503,0.980213,0.01658702],"study_design_scores_gemma":[0.0002139364,0.00003645915,0.003583233,0.0001226942,0.00002807373,0.00006414593,0.0000597582,0.002378948,0.005547968,0.002113791,0.9857765,0.00007443109],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001861751,0.0002476584,0.01580976,0.0005232748,0.0004424117,0.0004182976,0.6742203,0.2183266,0.08815006],"genre_scores_gemma":[0.01812595,0.0002197683,0.02052653,0.0007206169,0.0002976455,0.0009982969,0.8299125,0.07012792,0.05907081],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4501145,"threshold_uncertainty_score":0.7843449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1099158395599121,"score_gpt":0.2654929256281414,"score_spread":0.1555770860682293,"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."}}