{"id":"W6930904857","doi":"10.5281/zenodo.15755242","title":"Otsekülvi kasutus Eestis ja selle valikut mõjutavad tegurid tootjate küsitlusuuringu andmetel","year":2025,"lang":"et","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation Cluster (Canada)","funders":"","keywords":"European commission; Work (physics); Commission; Horizon","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001622698,0.00074422,0.0007103316,0.001039592,0.003957032,0.003708821,0.004936609,0.0004015669,0.05536299],"category_scores_gemma":[0.001448574,0.0007928868,0.0002612963,0.00180772,0.0003331591,0.0003676626,0.005604768,0.001541713,0.04622626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003109897,"about_ca_system_score_gemma":0.00005461965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003182893,"about_ca_topic_score_gemma":0.000001722364,"domain_scores_codex":[0.9936526,0.001394221,0.0007390326,0.001857818,0.00113045,0.00122581],"domain_scores_gemma":[0.9960161,0.0001116706,0.0005279244,0.001911549,0.0009030635,0.000529657],"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":[0.00003743829,0.0002704209,0.000006085344,0.0003741894,0.0002143723,0.0001495783,0.001261306,0.0003700836,0.0003086177,0.005390936,0.5444902,0.4471268],"study_design_scores_gemma":[0.0009003779,0.0004072416,0.0002215346,0.0004367534,0.00006775466,0.0001766161,0.00008539995,0.01174189,0.0002294393,0.0002405595,0.9846968,0.0007956287],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0002312341,0.000841477,0.07401596,0.001471724,0.001104024,0.0009120592,0.0005799318,0.002792887,0.9180507],"genre_scores_gemma":[0.01133431,0.0009789484,0.007392348,0.0006062306,0.001701015,2.20589e-7,0.001961267,0.006875517,0.9691501],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4463312,"threshold_uncertainty_score":0.9994522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02053293904549319,"score_gpt":0.2446438994059015,"score_spread":0.2241109603604083,"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."}}