{"id":"W6924988081","doi":"10.16904/envidat.199","title":"Predicted cloud droplet numbers Davos Wolfgang","year":2020,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Aerosol; Bin; Supersaturation; Particle (ecology); Wind speed; Particle number","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001215317,0.0002215928,0.0002684501,0.00005120708,0.0001561426,0.0008431294,0.00358341,0.0001078982,0.000713122],"category_scores_gemma":[0.00002399071,0.0002316893,0.00007521141,0.0005622742,0.00003664424,0.0002599589,0.001833713,0.0003214097,0.005888226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003852829,"about_ca_system_score_gemma":0.0003615943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001481495,"about_ca_topic_score_gemma":0.00005001246,"domain_scores_codex":[0.9984007,0.00005449074,0.0002920529,0.0007061033,0.0003466114,0.0001999759],"domain_scores_gemma":[0.9984356,0.0001273517,0.0002197854,0.0009565581,0.00008220167,0.0001784802],"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":[0.000002512198,0.00005401271,4.362488e-7,0.000007507975,0.00002547995,0.00001318376,0.00007888238,0.00005693869,0.000005235199,0.0004953395,0.985684,0.01357648],"study_design_scores_gemma":[0.0001769792,0.00002749247,0.00001692325,0.00002334998,0.0000224477,0.000006362818,0.000005346319,0.003261199,0.00001553573,0.001249403,0.9949363,0.000258628],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001316101,0.000009775902,0.01682526,0.001396422,0.0004210141,0.000557695,0.978534,0.000007910372,0.002234744],"genre_scores_gemma":[0.00007875534,0.00001077049,0.01913187,0.0004905699,0.0004383494,0.00005970152,0.9794725,0.00001129818,0.000306207],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01331785,"threshold_uncertainty_score":0.9948858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03372421184731816,"score_gpt":0.305310165687495,"score_spread":0.2715859538401768,"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."}}