{"id":"W4322756690","doi":"10.5281/zenodo.7691326","title":"Condensed Results Report of PROTECT's Legal Research","year":2023,"lang":"en","type":"report","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"European Law and Migration","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Horizon 2020 Framework Programme; European Commission","keywords":"Computer security; 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":[0.02014589,0.000798594,0.0008900262,0.008582941,0.005142772,0.009884899,0.001867737,0.003156901,0.06924616],"category_scores_gemma":[0.02984489,0.0007029769,0.00108279,0.01200834,0.003474195,0.004729696,0.006203338,0.003750924,0.02641232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01034739,"about_ca_system_score_gemma":0.01929655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02731946,"about_ca_topic_score_gemma":0.02061557,"domain_scores_codex":[0.976872,0.005343569,0.0008257609,0.001640691,0.01347873,0.001839229],"domain_scores_gemma":[0.9773924,0.009004374,0.0007481928,0.003978571,0.007762263,0.001114229],"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":[0.0001334698,0.0002099236,0.003138814,0.0007833487,0.00002366772,0.0003731012,0.00589526,0.0006539499,0.0008764435,0.3130658,0.57599,0.09885645],"study_design_scores_gemma":[0.000008526739,0.00003115741,0.003397141,0.000312962,0.000007487376,0.0001381902,0.001770609,0.00009710341,0.0008598936,0.007640992,0.9857184,0.00001755816],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01526028,0.005338237,0.005552876,0.01795662,0.002054679,0.001404331,0.0348126,0.0003621735,0.9172581],"genre_scores_gemma":[0.134328,0.01354451,0.02718951,0.01335845,0.001921852,0.005164282,0.05430758,0.001552323,0.7486336],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.06924616,"threshold_uncertainty_score":0.2316515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.23443764393457,"score_gpt":0.3999884274836882,"score_spread":0.1655507835491182,"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."}}