{"id":"W4233188278","doi":"10.14322/publons.r3508881","title":"10.14322/publons.r3508881","year":2000,"lang":"en","type":"dataset","venue":"Time to knit","topic":"Human Resource and Talent Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Core (optical fiber); Knowledge management; Computer science; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001076057,0.002561775,0.001461866,0.003926958,0.00073219,0.003590179,0.003137252,0.002296857,0.2787628],"category_scores_gemma":[0.004765505,0.001085298,0.001040671,0.008482768,0.0004965106,0.001714296,0.002583556,0.001399858,0.533569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001465039,"about_ca_system_score_gemma":0.00190177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02733397,"about_ca_topic_score_gemma":0.04037088,"domain_scores_codex":[0.9989645,0.0001245658,0.0001100791,0.0003330157,0.0002268265,0.0002410071],"domain_scores_gemma":[0.9979709,0.0003313793,0.0002623069,0.000571819,0.0005421726,0.0003214958],"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":[0.00003893602,0.00001602552,0.0004800834,0.0002831766,0.00001397631,0.000009228045,0.00001502151,0.0001396539,0.00006274723,0.0002515658,0.9967841,0.001905668],"study_design_scores_gemma":[0.0002168378,0.00002542338,0.003329764,0.0001940093,0.00002127706,0.0000340302,0.00007453685,0.0003891341,0.0003427899,0.0007694766,0.9945734,0.00002930858],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007269013,0.00003693208,0.00004977477,0.00004259939,0.00001978578,0.000006203068,0.9982188,0.0005814481,0.0009716983],"genre_scores_gemma":[0.0002625575,0.00003618816,0.0001086032,0.00003405641,0.000007253449,0.00003024961,0.9976041,0.0001430628,0.001773994],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7212372,"threshold_uncertainty_score":0.9325545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008181210850951562,"score_gpt":0.172758886538164,"score_spread":0.1645776756872124,"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."}}