{"id":"W4393630191","doi":"10.5281/zenodo.7604277","title":"Data-files-Annau-2023","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; University of Victoria","funders":"","keywords":"Computer science; Database","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":[],"consensus_categories":[],"category_scores_codex":[0.001504298,0.002102465,0.001504037,0.002992658,0.001193746,0.003189632,0.003021472,0.001744186,0.1826917],"category_scores_gemma":[0.006638767,0.0008428234,0.001180098,0.00483311,0.0005690649,0.002082973,0.002691122,0.002228511,0.3010948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001644484,"about_ca_system_score_gemma":0.002276102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008550566,"about_ca_topic_score_gemma":0.01178894,"domain_scores_codex":[0.9987606,0.0001941411,0.0001469468,0.0003643641,0.00034172,0.0001922596],"domain_scores_gemma":[0.9972329,0.0006921018,0.0002138253,0.0008731857,0.0006703984,0.0003176991],"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":[0.00004558999,0.00001816106,0.0003055916,0.0003588102,0.00001478035,0.00001438439,0.0000183692,0.0001648928,0.0001695341,0.0006575081,0.9964622,0.001770178],"study_design_scores_gemma":[0.00008556461,0.00001368662,0.001347827,0.0001282045,0.00001323433,0.00005773882,0.0000506524,0.0002660526,0.0007547433,0.001684891,0.9955733,0.00002399452],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008970773,0.00004347795,0.0001521411,0.00004997951,0.00003299468,0.00001807218,0.9967486,0.001478204,0.001386959],"genre_scores_gemma":[0.0003373626,0.00003798191,0.0004132325,0.00005689892,0.000007982341,0.00009879523,0.9976573,0.0004923895,0.0008979569],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1826917,"threshold_uncertainty_score":0.6111647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3152573172312619,"score_gpt":0.3949850451518419,"score_spread":0.07972772792058003,"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."}}