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Record W4411544705 · doi:10.1016/j.infbeh.2025.102099

The development of inductive reasoning during infancy

2025· article· en· W4411544705 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInfant Behavior and Development · 2025
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Children's Hospital Foundation
KeywordsInductive reasoningSimilarity (geometry)Focus (optics)Cognitive developmentCognitionPsychologyInductive methodCognitive psychologyLogical reasoningCognitive scienceDevelopmental psychologyComputer scienceArtificial intelligenceMathematics education

Abstract

fetched live from OpenAlex

Category-based inductive reasoning involves assuming that members of the same category share common properties. This form of reasoning allows individuals to draw upon previous knowledge, enhancing cognitive efficiency. This review paper focuses on the advances made in research on category-based inductive reasoning over the past 25 years, with specific focus on infants between the ages of 12 and 36 months. Three key lines of research are reviewed: studies demonstrating the role of shape similarity in guiding inferences, studies examining the conditions under which infants rely on shared labels to guide their inferencing, and studies examining how generic language statements guide toddlers' inductive inferences. Finally, directions for future research are discussed, with particular focus on the need to examine the developmental origins of inductive reasoning in infants younger than 12 months.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.306
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it