{"id":"W2971926688","doi":"10.1109/mcomstd.2019.8823834","title":"Standards for Open Source Development","year":2019,"lang":"en","type":"article","venue":"IEEE Communications Standards Magazine","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ericsson (Canada)","funders":"","keywords":"Open source; Engineering ethics; Computer science; Data science; Engineering; Programming language; Software","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.02286875,0.0002007389,0.0004068113,0.0003414119,0.0008632162,0.00192127,0.009589595,0.00005423859,0.0009268672],"category_scores_gemma":[0.00290629,0.0001648296,0.0001115925,0.001079871,0.0001747444,0.0005257585,0.004098993,0.0001642974,0.0008721635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004265955,"about_ca_system_score_gemma":0.001188644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000164196,"about_ca_topic_score_gemma":0.0002542869,"domain_scores_codex":[0.9948514,0.0002656285,0.0009942293,0.0008171264,0.002676123,0.0003955381],"domain_scores_gemma":[0.9881393,0.001509338,0.0003658254,0.00720017,0.002637097,0.0001483161],"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":[0.00009392651,0.0001431081,0.0008377607,0.00001375819,0.00004174799,3.159799e-7,0.0007052373,0.0004562662,0.0001434231,0.005266547,0.6836176,0.3086803],"study_design_scores_gemma":[0.001028299,0.00007005785,0.0008859971,0.00004745392,0.00001163389,0.000001965595,0.0003883825,0.007748104,0.0002039934,0.003517364,0.9858614,0.0002353063],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01608796,0.0006280401,0.7999611,0.006727976,0.002346074,0.003108389,0.00279439,0.0002532744,0.1680928],"genre_scores_gemma":[0.6775982,0.00005901346,0.1813813,0.0008845853,0.00009770744,0.0003019014,0.0003300103,0.00006551928,0.1392817],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6615102,"threshold_uncertainty_score":0.9999864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.164146930222637,"score_gpt":0.4500261588124295,"score_spread":0.2858792285897925,"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."}}