{"id":"W6908040303","doi":"10.25504/fairsharing.b3df6f","title":"FAIRsharing record for: Lunaris","year":2025,"lang":"en","type":"dataset","venue":"FAIRsharing.org","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multidisciplinary approach; Service (business); Interface (matter); Documentation; Data collection","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","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.001228244,0.001860854,0.002100288,0.00183134,0.00072515,0.0004293893,0.004092458,0.001898314,0.00206625],"category_scores_gemma":[0.002070273,0.002085092,0.00111531,0.001454234,0.0001987641,0.0005622652,0.003890504,0.002703379,0.006835405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001427223,"about_ca_system_score_gemma":0.0007656254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002934761,"about_ca_topic_score_gemma":0.003579257,"domain_scores_codex":[0.9917647,0.0001616334,0.00175884,0.00295604,0.001157028,0.002201742],"domain_scores_gemma":[0.9925256,0.0006145698,0.00120695,0.004581001,0.0005539907,0.0005179015],"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":[0.0002496443,0.0002449021,0.001652154,0.001929504,0.0006364007,0.00007518721,0.0000506305,0.00001888846,0.00007738469,0.00009625847,0.9944568,0.0005121909],"study_design_scores_gemma":[0.00154033,0.0001761699,0.0004670005,0.001503449,0.0008924708,0.00001538794,0.00008078471,0.0001041207,0.0002813399,0.0002331461,0.9927086,0.001997265],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001624521,0.0005571824,0.00006696154,0.0001778622,0.00402309,0.002339674,0.9871277,0.00122316,0.004321927],"genre_scores_gemma":[0.0001329197,0.0001605219,0.0007257375,0.000425201,0.001872571,0.001441699,0.9784099,0.000342658,0.01648882],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01216689,"threshold_uncertainty_score":0.9995974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04401742587751521,"score_gpt":0.3272946767283657,"score_spread":0.2832772508508505,"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."}}