{"id":"W4408438745","doi":"10.5194/egusphere-egu25-6110","title":"Icebergs, Genealogy and Jigsaw Puzzles","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Forensic and Genetic Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Jigsaw; Iceberg; Genealogy; Geography; History; Mathematics; Mathematics education; Meteorology; Sea ice","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":[],"consensus_categories":[],"category_scores_codex":[0.0001570193,0.0002103469,0.0002121009,0.00006309035,0.00005505312,0.00004271671,0.0002681675,0.000493238,0.00008141789],"category_scores_gemma":[0.00005632808,0.0001872737,0.00008723158,0.00003662184,0.0001935787,4.238149e-7,0.001778023,0.0002273455,0.00001035601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007730048,"about_ca_system_score_gemma":0.0002748325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001945355,"about_ca_topic_score_gemma":0.0003029693,"domain_scores_codex":[0.9987399,0.0000630517,0.0001861912,0.0006190465,0.0001234692,0.0002683234],"domain_scores_gemma":[0.9991508,0.00001367569,0.00004168974,0.0005955045,0.0001008395,0.00009756131],"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":[0.0003799961,0.0002273105,0.01252585,0.001606661,0.001421371,0.00003907473,0.0001927465,0.0007207535,0.1183815,0.01240987,0.6408918,0.211203],"study_design_scores_gemma":[0.001082276,0.0003739773,0.006574923,0.0001143104,0.0001010383,0.00004213131,0.0001391693,0.0007386723,0.1955336,0.008943881,0.7852961,0.001059971],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6825796,0.03495016,0.01398971,0.004134357,0.001569277,0.001374134,0.0003966703,0.00007347023,0.2609326],"genre_scores_gemma":[0.6692544,0.02320478,0.02656697,0.002583051,0.001428444,0.0002195128,0.002173517,0.00006962213,0.2744997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.210143,"threshold_uncertainty_score":0.76368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01293741673969155,"score_gpt":0.3045832947565628,"score_spread":0.2916458780168713,"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."}}