{"id":"W6969153130","doi":"10.5281/zenodo.7643309","title":"igfuw/UWLCM: Convergence paper","year":2023,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Semtech (Canada)","funders":"","keywords":"Convergence (economics); Variance (accounting); Code (set theory); Cloud computing; Range (aeronautics); Precipitation","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":[0.002199632,0.001736131,0.001307947,0.001712957,0.001447394,0.001781447,0.005803784,0.001927657,0.2212271],"category_scores_gemma":[0.007477176,0.001066267,0.001319113,0.002410466,0.0006191357,0.002383873,0.002480755,0.002599515,0.1520422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001958006,"about_ca_system_score_gemma":0.003239216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01808195,"about_ca_topic_score_gemma":0.01410486,"domain_scores_codex":[0.9981751,0.0003790296,0.0001082406,0.0003015541,0.0008107405,0.0002253078],"domain_scores_gemma":[0.9963554,0.0006138767,0.0001224124,0.0006809664,0.001981037,0.0002462668],"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":[0.0002283889,0.00008501954,0.0006515327,0.0003508196,0.00005080929,0.00006691449,0.0000831194,0.01579053,0.001143934,0.03072002,0.9067676,0.04406128],"study_design_scores_gemma":[0.0005394411,0.00005300636,0.001304552,0.0002590348,0.00004213937,0.0001639504,0.00007936719,0.2770567,0.01351606,0.02591566,0.6809528,0.0001172126],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.008749273,0.001203213,0.3057839,0.002119921,0.003270476,0.0008354603,0.2000402,0.1607653,0.3172322],"genre_scores_gemma":[0.06703785,0.0006250639,0.3064038,0.001025989,0.000512568,0.002627402,0.2458073,0.1982849,0.1776751],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.2212271,"threshold_uncertainty_score":0.7400784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03876391780050936,"score_gpt":0.2551353492939246,"score_spread":0.2163714314934152,"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."}}