{"id":"W4253948226","doi":"10.1515/iupac.73.0141","title":"Chips","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Modular Robots and Swarm Intelligence","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan College","funders":"","keywords":"Table (database); Product (mathematics); Commission; Food science; Chemistry; Biochemistry; Organic chemistry; Polymer science; Computer science; Mathematics; Political science; Database; Law","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002209802,0.0004050933,0.0004556633,0.0001455108,0.00005347367,0.00004904613,0.0004603427,0.0003319597,0.004937327],"category_scores_gemma":[0.00009953373,0.0003053918,0.000130422,0.0001091187,0.00006004361,0.00006073148,0.00007310934,0.0004567794,0.00001596295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002296208,"about_ca_system_score_gemma":0.0001158416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000265555,"about_ca_topic_score_gemma":0.0002378495,"domain_scores_codex":[0.9982754,0.00002222503,0.0003665334,0.0003059015,0.0006203059,0.0004096283],"domain_scores_gemma":[0.9988443,0.00003577172,0.00005360999,0.0007788793,0.0001372255,0.0001501857],"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":[0.000008471753,0.00002458316,6.760387e-7,0.000148214,0.00007322227,0.00004371945,0.000005063427,0.0002114306,0.00001126511,0.00001120003,0.9874733,0.01198882],"study_design_scores_gemma":[0.0001450712,0.00004191438,0.0000039878,0.0002506405,0.00003656385,0.00001297344,0.000003370247,0.0001234491,0.0001191523,0.0001172442,0.9987228,0.0004228164],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002234374,0.001542929,0.006345114,0.00007633378,0.001563423,0.0001510123,0.9899085,0.0002286574,0.0001617479],"genre_scores_gemma":[0.00003915093,0.003461346,0.00006619999,0.00007437647,0.001014985,0.00001026811,0.9949692,0.00006440416,0.0003000382],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.011566,"threshold_uncertainty_score":0.9999398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01452344376067444,"score_gpt":0.3564329064451622,"score_spread":0.3419094626844878,"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."}}