{"id":"W6921157341","doi":"10.6084/m9.figshare.6199211.v1","title":"Viitorul a început în trecut","year":2018,"lang":"ro","type":"article","venue":"Figshare","topic":"Computability, Logic, AI Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Product (mathematics); Context (archaeology); Identification (biology)","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002556298,0.0006306263,0.0005740018,0.0002089443,0.0005310974,0.0009723718,0.003509726,0.0003877007,0.2656382],"category_scores_gemma":[0.00167373,0.0006352937,0.0003485444,0.001380813,0.0001118952,0.0008007709,0.002969047,0.000537284,0.06124172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002904509,"about_ca_system_score_gemma":0.0005816343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005451326,"about_ca_topic_score_gemma":0.00006918779,"domain_scores_codex":[0.9951063,0.0002799903,0.0006652712,0.001740818,0.0009371798,0.001270479],"domain_scores_gemma":[0.9954462,0.0005459492,0.000324598,0.002278078,0.0008764753,0.0005286834],"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":[0.00001244586,0.0002767783,0.00007905962,0.0001801781,0.00004274766,0.0001122322,0.001822782,0.00002272637,0.0000357216,0.00017298,0.816631,0.1806113],"study_design_scores_gemma":[0.0006284215,0.0009582108,0.006983177,0.001549613,0.0000191511,0.00009822316,0.00004320586,0.1650393,0.001463993,0.001432712,0.8206781,0.001105884],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.005123382,0.01033546,0.0194124,0.01122543,0.0308791,0.007128776,0.7090555,0.006766526,0.2000734],"genre_scores_gemma":[0.8472346,0.00002836841,0.05089629,0.007210212,0.03686395,0.0008474761,0.03821607,0.0003803847,0.01832262],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8421112,"threshold_uncertainty_score":0.9996098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05138828752627546,"score_gpt":0.2820186541869926,"score_spread":0.2306303666607172,"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."}}