{"id":"W4393894029","doi":"10.5281/zenodo.6385204","title":"OpenAIRE Research Graph: Dump of funded products","year":2022,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission","keywords":"Graph; Computer science; Business; Theoretical computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001828197,0.001412383,0.001085807,0.01395562,0.0009128324,0.004345785,0.00161925,0.001582473,0.07631799],"category_scores_gemma":[0.01517525,0.0007720463,0.001123928,0.02115135,0.0004631346,0.00277169,0.002460181,0.001642909,0.07926663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002367119,"about_ca_system_score_gemma":0.00423124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02673991,"about_ca_topic_score_gemma":0.02908025,"domain_scores_codex":[0.9974529,0.0003119596,0.0003731265,0.0005478378,0.001070975,0.0002431614],"domain_scores_gemma":[0.9892201,0.003346853,0.0009380195,0.002396665,0.003379549,0.0007188497],"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":[0.0001314255,0.00002574315,0.001272983,0.0008454667,0.00002563122,0.00004986705,0.00009326873,0.0004547404,0.0003392869,0.002482635,0.9822193,0.01205953],"study_design_scores_gemma":[0.00004203969,0.0000127117,0.002686407,0.0001711101,0.00001133087,0.00004222472,0.0001335694,0.0003240971,0.0004519412,0.001646971,0.9944568,0.00002082235],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002782074,0.00007891841,0.0003410392,0.0001373732,0.00005601706,0.00002527033,0.995353,0.001451827,0.0022785],"genre_scores_gemma":[0.0009233198,0.0001668899,0.001754819,0.00006210681,0.00001936561,0.0000839613,0.994122,0.0007143684,0.00215314],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.07631799,"threshold_uncertainty_score":0.2553091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04959454017074114,"score_gpt":0.2917800240218341,"score_spread":0.242185483851093,"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."}}