{"id":"W6893132917","doi":"10.5281/zenodo.14710297","title":"INSTAR - QR cards","year":2025,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"QR Code Applications and Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Commission","keywords":"Key (lock); Information technology; Digital economy; Emerging technologies","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00265506,0.001258418,0.0009845796,0.002659978,0.001459049,0.006495047,0.002295564,0.002017207,0.385797],"category_scores_gemma":[0.01470548,0.0008494112,0.0005113319,0.002350233,0.001189224,0.005554819,0.004564628,0.001929897,0.327181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001189763,"about_ca_system_score_gemma":0.001998397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001314578,"about_ca_topic_score_gemma":0.00136821,"domain_scores_codex":[0.9957864,0.0009286662,0.0003151844,0.0005537416,0.001923147,0.0004929132],"domain_scores_gemma":[0.9900804,0.001458668,0.0005243056,0.002980335,0.004351435,0.0006048927],"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":[0.001145726,0.0001310417,0.0007974797,0.0003013524,0.00001251426,0.0001886878,0.0002067054,0.0003563138,0.004222948,0.09182958,0.70955,0.1912577],"study_design_scores_gemma":[0.000106326,0.0001510736,0.0003974209,0.0001054765,0.00001195275,0.0003776057,0.000107613,0.002738149,0.006746228,0.008051675,0.9811592,0.00004727471],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.008780037,0.001019052,0.157207,0.002739445,0.00380561,0.001566976,0.02060847,0.09769543,0.706578],"genre_scores_gemma":[0.0828331,0.0008310299,0.1347415,0.002472081,0.0009325013,0.001146433,0.03038961,0.0141059,0.7325479],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.385797,"threshold_uncertainty_score":0.8760861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02366836551670544,"score_gpt":0.2453922726711087,"score_spread":0.2217239071544033,"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."}}