{"id":"W6969596785","doi":"10.5281/zenodo.6860470","title":"Wie sich Business-to-Business-Sharing gezielt unterstützen lässt","year":2022,"lang":"de","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Digital Innovation in Industries","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Work (physics); Quarter (Canadian coin); Order (exchange); Context (archaeology)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001500623,0.0004811,0.0004064183,0.001533758,0.007812074,0.009115591,0.003298496,0.0001222959,0.06641925],"category_scores_gemma":[0.002228157,0.0006053569,0.00009406189,0.009347075,0.0002655047,0.002616547,0.01367018,0.0008345111,0.04847837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005596701,"about_ca_system_score_gemma":0.00002030764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001737183,"about_ca_topic_score_gemma":7.197237e-7,"domain_scores_codex":[0.995565,0.000119478,0.0008591644,0.001166008,0.001296993,0.0009933552],"domain_scores_gemma":[0.9945455,0.00003822198,0.0005512555,0.001070511,0.003683357,0.0001111615],"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":[0.0002551785,0.0004815856,0.0002619767,0.000485589,0.0001985455,0.00008510261,0.0006305167,0.002401746,0.0005947003,0.0328934,0.9275795,0.03413214],"study_design_scores_gemma":[0.0008002361,0.00007415302,0.004675874,0.0001368841,0.00007841363,0.00003392382,0.001244319,0.0006348659,0.0000202512,0.0004878867,0.9911498,0.00066334],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1041413,0.0008241406,0.005546865,0.03937698,0.007506394,0.003729262,0.001933887,0.005224842,0.8317164],"genre_scores_gemma":[0.9514253,0.00006719829,0.0001337598,0.005866032,0.004550418,0.000001292331,0.01401329,0.005666243,0.01827649],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.847284,"threshold_uncertainty_score":0.9996398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05335022683647526,"score_gpt":0.236936423781316,"score_spread":0.1835861969448408,"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."}}