{"id":"W6936562659","doi":"10.58079/b6ni","title":"AàC | Animal et animalité | 15 déc. 2018","year":2018,"lang":"fr","type":"article","venue":"OpenEdition (OpenEdition)","topic":"Animal Law and Welfare","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Identification (biology); Context (archaeology); Set (abstract data type); Selection (genetic algorithm)","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":["metaepi_narrow","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["sts","insufficient_payload"],"category_scores_codex":[0.001885259,0.0006890182,0.0006878683,0.0001743252,0.00269434,0.0007713195,0.001031291,0.0007455808,0.06677585],"category_scores_gemma":[0.0002893398,0.0007631272,0.0003694075,0.001180217,0.002842838,0.02114737,0.0003778324,0.0006089196,0.02802413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004809941,"about_ca_system_score_gemma":0.0006921595,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003179974,"about_ca_topic_score_gemma":0.02123973,"domain_scores_codex":[0.9938549,0.001087439,0.0009713373,0.001232548,0.001450023,0.001403767],"domain_scores_gemma":[0.9967521,0.0002808461,0.0005494519,0.0006349911,0.0009716882,0.0008108772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000209608,0.0003804235,0.0002085605,0.00004891758,0.00007653874,0.00006870965,0.0009663755,0.000001952806,0.0003213307,0.7750836,0.2200892,0.002544739],"study_design_scores_gemma":[0.0009823346,0.001820332,0.03259395,0.0003197327,0.0001686126,0.00006241615,0.002044155,0.00006517366,0.0008574034,0.009312242,0.9507867,0.000986933],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03269894,0.003006461,0.0007230734,0.3606583,0.01072235,0.001216188,0.001912521,0.0003821696,0.5886799],"genre_scores_gemma":[0.8684667,0.0008453412,0.001523407,0.06282378,0.01029727,0.0001703002,0.0007801526,0.0000989079,0.05499419],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8357677,"threshold_uncertainty_score":0.9998708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03174231653438597,"score_gpt":0.3040309818915222,"score_spread":0.2722886653571363,"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."}}