{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001999976,0.001486472,0.001656582,0.005106721,0.003375525,0.007331796,0.004323561,0.001886431,0.4762533],"category_scores_gemma":[0.01256826,0.0008391508,0.0009841893,0.009600235,0.001021807,0.005142265,0.005176065,0.002197108,0.4823936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004460446,"about_ca_system_score_gemma":0.008445946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1375951,"about_ca_topic_score_gemma":0.2116972,"domain_scores_codex":[0.9980572,0.0001790019,0.000127157,0.0004706687,0.0008120978,0.0003537368],"domain_scores_gemma":[0.9924137,0.0008465849,0.0002480571,0.002731752,0.002470706,0.001289242],"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":[0.00001064964,0.000002991184,0.0000507994,0.00002482525,0.000001405905,0.000003375269,0.000006474533,0.00001023352,0.00001375983,0.0002091089,0.9988103,0.0008560407],"study_design_scores_gemma":[0.00003226007,0.000003138795,0.0005917196,0.00005086609,0.000002398692,0.00001220083,0.00004127334,0.00006817607,0.00009136044,0.0007332464,0.9983605,0.00001281261],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001327136,0.00005859289,0.0001251622,0.0005512724,0.0002011811,0.00002985408,0.9845553,0.002591701,0.01175427],"genre_scores_gemma":[0.0005251449,0.00007665073,0.0003521407,0.000324604,0.00004151969,0.00007528001,0.980291,0.001173441,0.01714028],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4762533,"threshold_uncertainty_score":0.747061,"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."}}