{"id":"W6891904179","doi":"10.48579/pro/afxqrn/ccj14t","title":"Chain tension.FCStd","year":2023,"lang":"en","type":"dataset","venue":"data.InDoRES","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Nautical Research Society","funders":"","keywords":"Chain (unit); Yield (engineering); Product (mathematics); Sequence (biology)","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","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001804344,0.001043722,0.001194654,0.001165746,0.0003296739,0.0003277288,0.006589483,0.0008126495,0.0009399984],"category_scores_gemma":[0.003245082,0.0009530158,0.0001755904,0.001377333,0.0003753752,0.0005082022,0.006790895,0.001564379,0.4985875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001992675,"about_ca_system_score_gemma":0.0004381477,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008500525,"about_ca_topic_score_gemma":0.008551113,"domain_scores_codex":[0.9934157,0.0003967993,0.0009147386,0.002305638,0.001700843,0.001266338],"domain_scores_gemma":[0.9871472,0.0006522617,0.0006523926,0.01098905,0.0001669923,0.000392112],"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":[0.00007611135,0.0001356583,0.00001411061,0.0002074648,0.0002735184,0.001113308,0.00001099539,0.000006514667,0.00006147451,0.00001128515,0.997827,0.00026254],"study_design_scores_gemma":[0.0006807234,0.00005346991,0.0004168559,0.0003117662,0.0003361986,0.00005706703,0.00005215788,0.0001278171,0.00001362524,0.00009984432,0.9967826,0.001067892],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00002111301,0.0005783876,0.000001804627,0.0002145958,0.00219254,0.0007987299,0.9952146,0.0009155008,0.0000627155],"genre_scores_gemma":[0.000001866637,0.0006665596,0.0001379437,0.0004604881,0.001973703,0.000108248,0.9951347,0.0004602992,0.001056159],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4976475,"threshold_uncertainty_score":0.9999733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08863389858077378,"score_gpt":0.3418598151959483,"score_spread":0.2532259166151746,"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."}}