{"id":"W6913110027","doi":"10.5281/zenodo.8092498","title":"nanograv/pint_pal: Release on PyPi","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":"University of British Columbia","funders":"National Science Foundation","keywords":"Template; Metadata; Transparency (behavior); Process (computing); Static timing analysis; Work (physics)","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":[0.002876907,0.002079139,0.001479917,0.002476068,0.001240766,0.003855693,0.00341964,0.001220364,0.2567081],"category_scores_gemma":[0.009160309,0.002068137,0.001314011,0.003010512,0.0006138108,0.005593605,0.004167853,0.003468055,0.2899162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001431682,"about_ca_system_score_gemma":0.002440694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004191035,"about_ca_topic_score_gemma":0.00341299,"domain_scores_codex":[0.9983847,0.0001372055,0.0001279264,0.0003375981,0.0008403586,0.0001722193],"domain_scores_gemma":[0.9963443,0.000572728,0.0002354868,0.001467204,0.001096921,0.0002833428],"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":[0.0003067368,0.00004864764,0.000511635,0.0004431611,0.00004500836,0.00008052323,0.0001139495,0.0006962498,0.004575729,0.004825001,0.9238536,0.06449962],"study_design_scores_gemma":[0.00006191535,0.00002300374,0.0007927705,0.0000768651,0.00001817879,0.00008529224,0.00002529191,0.001624631,0.0107641,0.003589601,0.9828545,0.00008378097],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.002659061,0.0005468024,0.1094147,0.0009856424,0.001103237,0.0003162198,0.2682045,0.5221015,0.09466843],"genre_scores_gemma":[0.01280496,0.0006859711,0.07951505,0.000777403,0.0002556345,0.001297955,0.3477513,0.4607424,0.09616935],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.2567081,"threshold_uncertainty_score":0.8587743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0420692277361652,"score_gpt":0.2623219773363533,"score_spread":0.2202527496001881,"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."}}