{"id":"W2042253916","doi":"10.1155/2014/797348","title":"Collective Mind: Towards Practical and Collaborative Auto-Tuning","year":2014,"lang":"en","type":"article","venue":"Scientific Programming","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Google (Canada)","funders":"Soochow University","keywords":"Computer science; Benchmarking; Modular design; Set (abstract data type); Distributed computing; Software; Code (set theory); Data science; Software engineering; Artificial intelligence; Machine learning","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"],"consensus_categories":[],"category_scores_codex":[0.001734189,0.0001439168,0.0001694851,0.0002154893,0.0007799377,0.00168404,0.0003894159,0.00006878602,0.000004052974],"category_scores_gemma":[0.0005890346,0.0001345249,0.00003242238,0.001457822,0.0002652302,0.0005523668,0.0003532395,0.0001628617,0.00001305835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008645152,"about_ca_system_score_gemma":0.0006949416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006435675,"about_ca_topic_score_gemma":0.000005667279,"domain_scores_codex":[0.998193,0.0001997007,0.0002149673,0.0006692522,0.0003531664,0.0003699311],"domain_scores_gemma":[0.9988112,0.0001635466,0.0001383359,0.0003917623,0.0003450529,0.0001500992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008130547,0.0001103802,0.0002525396,0.00001689105,0.00002233388,0.000009672611,0.008493067,0.0001746782,0.0005504805,0.04278746,0.002629516,0.9449449],"study_design_scores_gemma":[0.000328943,0.0002107181,0.0002034221,0.00004985564,0.000009957552,0.0000364245,0.0002027106,0.8155527,0.00455134,0.007269478,0.1712343,0.0003500941],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002615736,0.00008806219,0.9903268,0.0009450949,0.0004606298,0.0002870665,8.689286e-7,0.00046294,0.004812776],"genre_scores_gemma":[0.2241233,0.000001547204,0.7744756,0.00005922097,0.00003419909,0.00002821704,0.000002880787,0.00000691677,0.001268128],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9445947,"threshold_uncertainty_score":0.9993523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02262732856723581,"score_gpt":0.3007937580503889,"score_spread":0.2781664294831531,"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."}}